MyHeritage Updates Theories of Family Relativity – Who is Waiting for You?

I always love to receive e-mails from Daniel Horowitz, Genealogy Expert at MyHeritage, because I know there is always something good waiting for me.

Today, it was the announcement that MyHeritage has refreshed the Theories of Family Relativity database again. The last time was mid-May.

If you recall, Theories of Family Relativity (TOFR) provide you with theories, aka, hints, as to how you and other people whose DNA you match may be related to each other – through which common ancestor.

According to Daniel:

Since the last update, the number of theories on MyHeritage has grown by 64%, from 20,330,031 to 33,373,070! The number of MyHeritage users who now have at least one Theory of Family Relativity™ for their DNA Matches has increased by 28%.

MyHeritage reruns the connections periodically and updates customer results.

By signing on to your account and clicking on “View Theories,” you can view only the matches that have an associated theory.

I have a total of 67 theories, 5 of which are new.

In my case, I create a note for each match, so I can scroll down my match list and easily identify which people have new TOFR

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You can see in the screenshot that my match, David, has a note, indicated by the purple icon, but Sarah does not. She also has a “New” indication for the TOFR which will remain for 30 days.

I’m excited. I can’t guess based on the 13 people in her tree how we might be connected, which is a little game I like to play, so I’m going to have to click on “View Theory” to make that discovery.

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Aha – William Crumley through daughter Mary who married William Testerman. I’m glad to see this, and I suspect this new connection may be due to the fact that I optimized my trees to enable TOFR to make connections by adding all of the children and grandchildren of my ancestors, with their spouses. This facilitates the “spanning trees” connections, indicated by the red arrows above, where Mary Brown “Polly” Crumley 1803-1881 connects in another tree with Mary Brown 1803-1881 and then further down that tree, James Harold Mitchell 1899-1961 connects with James Harold Mitchell born 1899-deceased. In other words, the theory is that these are the same people and those connections allow us to “cross and connect trees” and walk down them like a genealogical ladder.

Now, of course, I need to verify the connection both genetically and genealogically as well as reach out to my new cousin.

Sarah only has 13 people in her tree. She might be a new researcher. I’d like to provide her with my articles about our common ancestor, assuming the connection verifies. There were multiple William Crumleys and there is a lot of misinformation out there, waiting for unsuspecting genealogists. Maybe my articles will help her avoid the sand traps I landed in and who knows what information she might have to share. Like, if there is a graveyard on her Testerman ancestor’s property – which might be where William is buried. You never know and hope springs eternal!

If you already have DNA results at MyHeritage, sign in, and see if you have new Theories of Family Relativity.

If you don’t have DNA results there, you can transfer from elsewhere for free by clicking here and then either try a trial MyHeritage subscription, here or unlock the advanced features that include TOFR for $29. Or you can order a DNA test from MyHeritage, here.

We don’t know in advance when MyHeritage is going to refresh the database for new TOFR connections, so it’s important to be in the database when that happens.

If you’d like to know more about Theories of Family Relativity, I wrote about how to work with them here, here, and here.

Have fun!!!

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442 Ancient Viking Skeletons Hold DNA Surprises – Does Your Y or Mitochondrial DNA Match? Daily Updates Here!

Yesterday, in the journal Nature, the article “Population genomics of the Viking world,” was published by Margaryan, et al, a culmination of 6 years of work.

Just hours later, Science Daily published the article, “World’s largest DNA sequencing of Viking skeletons reveals they weren’t all Scandinavian.” Science magazine published “’Viking’ was a job description, not a matter of heredity, massive ancient DNA study shows.” National Geographic wrote here, and CNN here.

Vikings Not All Scandinavian – Or Blonde

Say what??? That’s not at all what we thought we knew. That’s the great thing about science – we’re always learning something new.

442 Viking skeletons from outside Scandinavia were sequenced by Eske Willerslev’s lab, producing whole genome sequences for both men and women from sites in Scotland, Ukraine, Poland, Russia, the Baltic, Iceland, Greenland and elsewhere in continental Europe. They were then compared to known Viking samples from Scandinavia.

Not the grave where the sample was taken, but a Viking cemetery from Denmark.

One Viking boat burial in an Estonian Viking cemetery shows that 4 Viking brothers died and were buried together, ostensibly perishing in the same battle, on the same day. Based on their DNA, the brothers probably came from Sweden.

Vikings raiding parties from Scandinavia originated in Norway, Sweden and Denmark. At least some Viking raiders seem to be closely related to each other, and females in Iceland appear to be from the British Isles, suggesting that they may have “become” Vikings – although we don’t really understand the social and community structure.

Genes found in Vikings were contributed from across Europe, including southern Europe, and as afar away as Asia. Due to mixing resulting from the Viking raids beginning at Lindisfarne in 793 , the UK population today carries as much as 6% Viking DNA. Surprisingly, Swedes had only 10%.

Some Viking burials in both Orkney and Norway were actually genetically Pictish men. Converts, perhaps? One of these burials may actually be the earliest Pict skeleton sequenced to date.

Y DNA

Of the 442 skeletons, about 300 were male. The whole genome sequence includes the Y chromosome along with mitochondrial DNA, although it requires special processing to separate it usefully.

Goran Runfeldt, a member of the Million Mito team and head of research at FamilyTreeDNA began downloading DNA sequences immediately, and Michael Sager began analyzing Y DNA, hoping to add or split Y DNA tree branches.

Given the recent split of haplogroup P and A00, these ancient samples hold HUGE promise.

Michael and Goran have agreed to share their work as they process these samples – providing a rare glimpse real-time into the lab.

You and the Tree

Everyone is so excited about this paper, and I want you to be able to see if your Y or mitochondrial DNA, or that of your relatives matches the DNA haplogroups in the paper.

The paper itself uses the older letter=number designations for Y DNA haplogroup, so FamilyTreeDNA is rerunning, aligning and certifying the actual SNPs. The column FTDNA Haplogroup reflects the SNP Y haplogroup name.

Note that new Y DNA branches appear on the tree the day AFTER the change is made, and right now, changes resulting from this paper are being made hourly. I will update the haplogroup information daily as more becomes available. Pay particular attention to the locations that show where the graves were found along with the FamilyTreeDNA notes.

Goran has also included the mtDNA haplogroup as identified in the paper. Mitochondrial DNA haplogroups have not been recalculated, but you just might see them in the Million Mito Project😊

Here’s what you’ll need to do:

  • Go to your Y or mitochondrial DNA results and find your haplogroup.

  • Do a browser search on this article to see if your haplogroup is shown. On a PC, that’s CTRL+F to show the “find” box. If your haplogroup isn’t showing, you could be downstream of the Viking haplogroup, so you’ll need to use the Y DNA Block Tree (for Big Y testers) or public haplotree, here.
  • If you’ve taken the Big Y test, click on the Block Tree on your results page and then look across the top of your results page to see if the haplogroup in question is “upstream” or a parent of your haplogroup.

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If you don’t see it, keep scanning to the left until you see the last SNP.

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  • If the haplogroup you are seeking is NOT shown in your direct upstream branches, you can type the name of the haplogroup into the search box. For example, I’ve typed I-BY3428. You can also simply click on the FTDNA name haplogroup link in the table, below, considerately provided by Goran.

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I don’t see the intersecting SNP yet, between the tester and the ancient sample, so if I click on I-Y2592, I can view the rest of the upstream branches of haplogroup I.

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By looking at the Y DNA SNPs of the tester, and the Y DNA SNPs of the ancient sample, I can see that the intersecting SNP is DF29, roughly 52 SNP generations in the past. Rule of thumb is that SNP generations are 80-100 years each.

How About You – Are You Related to a Viking?

Below, you’ll find the information from Y DNA results in the paper, reprocessed and analyzed, with FamilyTreeDNA verified SNP names, along with the mitochondrial DNA haplogroup of each Viking male.

Are you related, and if so, how closely?

I was surprised to find a sister-branch to my own mitochondrial J1c2f. J1c2 and several subclades or branches were found in Viking burials.

I need to check all of my ancestral lines, both male and female. There’s history waiting to be revealed. What have you discovered?

Ancient Viking Sample Information

Please note that this information will be updated on business days until all samples have been processed and placed on the Y DNA tree – so this will be a “live” copy of the most current phylogenetic information.

Link to the locations to see the locations of the excavation sites, and the haplogroups for the tree locations. Michael Sager is making comments as he reviews each sample.

Enjoy!

Sample: VK14 / Russia_Ladoga_5680-12
Location: Ladoga, Russia
Age: Viking 10-12th centuries CE
Y-DNA: I-BY3428
mtDNA: J1c1a

Sample: VK16 / Russia_Ladoga_5680-2
Location: Ladoga, Russia
Age: Viking 11-12th centuries CE
Y-DNA: I-M253
mtDNA: X2b4

Sample: VK17 / Russia_Ladoga_5680-17
Location: Ladoga, Russia
Age: Viking 10-12th centuries CE
Y-DNA: T-Y138678
FTDNA Comment: Shares 5 SNPs with a man from Chechen Republic, forming a new branch down of T-Y22559 (T-Y138678)
mtDNA: U5a2a1b

Sample: VK18 / Russia_Ladoga_5680-3
Location: Ladoga, Russia
Age: Viking 10-12th centuries CE
Y-DNA: R-YP1370
mtDNA: H1b1

Sample: VK20 / Russia_Ladoga_5680-1
Location: Ladoga, Russia
Age: Viking 11th century CE
Y-DNA: I-Y22478
FTDNA Comment: Splits the I-Z24071 branch, positive only for Y22478. New path = I-Y22486>I-Y22478>I-Z24071
mtDNA: H6c

Sample: VK22 / Russia_Ladoga_5680-13
Location: Ladoga, Russia
Age: Viking 10-12th centuries CE
Y-DNA: I-A8462
mtDNA: T2b

Sample: VK23 / Russia_Ladoga_5680-9
Location: Ladoga, Russia
Age: Viking 10-12th centuries CE
Y-DNA: I-M253
mtDNA: U4a1a

Sample: VK24 / Faroe_AS34/Panum
Location: Hvalba, Faroes
Age: Viking 11th century
Y-DNA: R-FGC12948
mtDNA: J1b1a1a

Sample: VK25 / Faroe_1
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-FT381000
FTDNA Comment: Splits the R-BY11762 branch, positive for 5 variants ancestral for ~14, new path = R-A8041>R-BY11764>BY11762
mtDNA: H3a1a

Sample: VK27 / Faroe_10
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-L513
mtDNA: U5a1g1

Sample: VK29 / Sweden_Skara 17
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: I-S7642
mtDNA: T2b3b

Sample: VK30 / Sweden_Skara 105
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-S2857
mtDNA: U5b1c2b

Sample: VK31 / Sweden_Skara 194
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-L21
mtDNA: I4a

Sample: VK34 / Sweden_Skara 135
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-BY111759
mtDNA: HV-T16311C!

Sample: VK35 / Sweden_Skara 118
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-CTS4179
mtDNA: T2f1a1

Sample: VK39 / Sweden_Skara 181
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: G-Z1817
mtDNA: T2b4b

Sample: VK40 / Sweden_Skara 106
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-BY166438
FTDNA Comment: Shares 10 SNPs with a man with unknown origins (American) downstream of R-BY1701. New branch R-BY166438
mtDNA: T1a1

Sample: VK42 / Sweden_Skara 62
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: J-FGC32685
mtDNA: T2b11

Sample: VK44 / Faroe_17
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-S658
mtDNA: H3a1a

Sample: VK45 / Faroe_18
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-CTS8277
mtDNA: H3a1

Sample: VK46 / Faroe_19
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-BY202785
FTDNA Comment: Forms a branch with VK245 down of R-BY202785 (Z287). New branch = R-FT383000
mtDNA: H5

Sample: VK48 / Gotland_Kopparsvik-212/65
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-FGC52679
mtDNA: H10e

Sample: VK50 / Gotland_Kopparsvik-53.64
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: I-Y22923
mtDNA: H1-T16189C!

Sample: VK51 / Gotland_Kopparsvik-88/64
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: N-L1026
mtDNA: U5b1e1

Sample: VK53 / Gotland_Kopparsvik-161/65
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: I-CTS10228
mtDNA: HV9b

Sample: VK57 / Gotland_Frojel-03601
Location: Frojel, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-L151
mtDNA: J1c6

Sample: VK60 / Gotland_Frojel-00702
Location: Frojel, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-YP1026
mtDNA: H13a1a1b

Sample: VK64 / Gotland_Frojel-03504
Location: Frojel, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-BY58559
mtDNA: I1a1

Sample: VK70 / Denmark_Tollemosegard-EW
Location: Tollemosegård, Sealand, Denmark
Age: Early Viking Late Germanic Iron Age/early Viking
Y-DNA: I-BY73576
mtDNA: H7d4

Sample: VK71 / Denmark_Tollemosegard-BU
Location: Tollemosegård, Sealand, Denmark
Age: Early Viking Late Germanic Iron Age/early Viking
Y-DNA: I-S22349
mtDNA: U5a1a

Sample: VK75 / Greenland late-0929
Location: V051, Western Settlement, Greenland
Age: Late Norse 1300 CE
Y-DNA: R-P310
mtDNA: H54

Sample: VK87 / Denmark_Hesselbjerg Grav 41b, sk PC
Location: Hesselbjerg, Jutland, Denmark
Age: Viking 850-900 CE
Y-DNA: R-Z198
mtDNA: K1c2

Sample: VK95 / Iceland_127
Location: Hofstadir, Iceland
Age: Viking 10-13th centuries CE
Y-DNA: R-S658
mtDNA: H6a1a3a

Sample: VK98 / Iceland_083
Location: Hofstadir, Iceland
Age: Viking 10-13th centuries CE
Y-DNA: I-BY3433
FTDNA Comment: Splits I-BY3430. Derived for 1 ancestral for 6. New path = I-BY3433>I-BY3430
mtDNA: T2b3b

Sample: VK101 / Iceland_125
Location: Hofstadir, Iceland
Age: Viking 10-13th centuries CE
Y-DNA: R-BY110718
mtDNA: U5b1g

Sample: VK102 / Iceland_128
Location: Hofstadir, Iceland
Age: Viking 10-13th centuries CE
Y-DNA: R-Y96503
FTDNA Comment: Shares 3 SNPs with a man from Sweden. Forms a new branch downstream of R-FGC23826. New branch = R-Y96503
mtDNA: J1c3f

Sample: VK110 / Iceland_115S
Location: Hofstadir, Iceland
Age: Viking 10-13th centuries CE
Y-DNA: I-FGC21682
mtDNA: H10-x

Sample: VK117 / Norway_Trondheim_SK328
Location: Trondheim, Nor_Mid, Norway
Age: Medieval 12-13th centuries CE
Y-DNA: R-S9257
mtDNA: H1a3a

Sample: VK123 / Iceland_X104
Location: Hofstadir, Iceland
Age: Viking 10-13th centuries CE
Y-DNA: R-Y130994
FTDNA Comment: Shares 17 SNPs with a man from the UAE. Creates a new branch downstream of R2-V1180. New branch = R-Y130994
mtDNA: J1c9

Sample: VK127 / Iceland_HDR08
Location: Hringsdalur, Iceland
Age: Viking 10th century CE
Y-DNA: R-BY92608
mtDNA: H3g1b

Sample: VK129 / Iceland_ING08
Location: Ingiridarstadir, Iceland
Age: Viking 10th century CE
Y-DNA: R-BY154143
FTDNA Comment: Shares 3 SNPs with a man from Sweden. Forms a new branch downstream of R1a-YP275. New branch = R-BY154143
mtDNA: U5b1b1a

Sample: VK133 / Denmark_Galgedil KO
Location: Galgedil, Funen, Denmark
Age: Viking 8-11th centuries CE
Y-DNA: R-Z8
mtDNA: K1a4a1a3

Sample: VK134 / Denmark_Galgedil ALZ
Location: Galgedil, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: R-BY97519
mtDNA: H1cg

Sample: VK138 / Denmark_Galgedil AQQ
Location: Galgedil, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: R-S1491
mtDNA: T2b5

Sample: VK139 / Denmark_Galgedil ANG
Location: Galgedil, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: R-BY32008
mtDNA: J1c3k

Sample: VK140 / Denmark_Galgedil PT
Location: Galgedil, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: G-M201
mtDNA: H27f

Sample: VK143 / UK_Oxford_#7
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-Y13833
FTDNA Comment: Splits R-Y13816. Derived for 6 ancestral for 3. New path = R-Y13816>R-Y13833
mtDNA: U5b1b1-T16192C!

Sample: VK144 / UK_Oxford_#8
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-Y2592
mtDNA: V1a1

Sample: VK145 / UK_Oxford_#9
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-YP1708
mtDNA: H17

Sample: VK146 / UK_Oxford_#10
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-M6155
mtDNA: J1c3e1

Sample: VK147 / UK_Oxford_#11
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-Y75899
mtDNA: T1a1q

Sample: VK148 / UK_Oxford_#12
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-M253
mtDNA: H6a1a

Sample: VK149 / UK_Oxford_#13
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-M253
mtDNA: H1a1

Sample: VK150 / UK_Oxford_#14
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-FT4725
mtDNA: H1-C16239T

Sample: VK151 / UK_Oxford_#15
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-S19291
mtDNA: T2b4-T152C!

Sample: VK153 / Poland_Bodzia B1
Location: Bodzia, Poland
Age: Viking 10-11th centuries CE
Y-DNA: R-M198
mtDNA: H1c3

Sample: VK156 / Poland_Bodzia B4
Location: Bodzia, Poland
Age: Viking 10-11th centuries CE
Y-DNA: R-Y9081
mtDNA: J1c2c2a

Sample: VK157 / Poland_Bodzia B5
Location: Bodzia, Poland
Age: Viking 10-11th centuries CE
Y-DNA: I-S2077
mtDNA: H1c

Sample: VK159 / Russia_Pskov_7283-20
Location: Pskov, Russia
Age: Viking 10-11th centuries CE
Y-DNA: R-A7982
mtDNA: U2e2a1d

Sample: VK160 / Russia_Kurevanikka_7283-3
Location: Kurevanikha, Russia
Age: Viking 10-13th centuries CE
Y-DNA: R-YP1137
mtDNA: C4a1a-T195C!

Sample: VK163 / UK_Oxford_#1
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-M253
mtDNA: U2e2a1a1

Sample: VK165 / UK_Oxford_#3
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-S18218
mtDNA: U4b1b1

Sample: VK166 / UK_Oxford_#4
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-BY67003
FTDNA Comment: Splits R-BY45170 (DF27). Derived for 2, ancestral for 7. New path = R-BY67003>R-BY45170
mtDNA: H3ag

Sample: VK167 / UK_Oxford_#5
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-BY34674
mtDNA: H4a1a4b

Sample: VK168 / UK_Oxford_#6
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-Z18
mtDNA: H4a1a4b

Sample: VK170 / Isle-of-Man_Balladoole
Location: Balladoole, IsleOfMan
Age: Viking 9-10th centuries CE
Y-DNA: R-S3201
mtDNA: HV9b

Sample: VK172 / UK_Oxford_#16
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-FT7019
mtDNA: I1a1e

Sample: VK173 / UK_Oxford_#17
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-FT13004
FTDNA Comment: Splits I2-FT12648, derived for 5, ancestral for 7. New path FT13004>FT12648
mtDNA: U5a1b-T16362C

Sample: VK174 / UK_Oxford_#18
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-FGC17429
mtDNA: H1-C16239T

Sample: VK175 / UK_Oxford_#19
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-Y47841
FTDNA Comment: Shares 6 SNPs with man from Sweden down of R-BY38950 (R-Y47841)
mtDNA: H1a1

Sample: VK176 / UK_Oxford_#20
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: I-FT3562
mtDNA: H10

Sample: VK177 / UK_Oxford_#21
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-FT31867
FTDNA Comment: Shares 3 SNPs with a man from Greece. Forms a new branch downstream of R-BY220332 (U152). New branch = R-FT31867
mtDNA: H82

Sample: VK178 / UK_Oxford_#22
Location: St_John’s_College_Oxford, Oxford, England, UK
Age: Viking 880-1000 CE
Y-DNA: R-BY176639
FTDNA Comment: Links up with PGA3 (Personal Genome Project Austria) and FTDNA customer from Denmark. PGA and FTDNA customer formed a branch earlier this week, VK178 will join them at R-BY176639 (Under L48)
mtDNA: K2a5

Sample: VK179 / Greenland F2
Location: Ø029a, Eastern Settlement, Greenland
Age: Early Norse 10-12th centuries CE
Y-DNA: I-F3312
mtDNA: K1a3a

Sample: VK183 / Greenland F6
Location: Ø029a, Eastern Settlement, Greenland
Age: Early Norse 10-12th centuries CE
Y-DNA: I-F3312
mtDNA: T2b21

Sample: VK184 / Greenland F7
Location: Ø029a, Eastern Settlement, Greenland
Age: Early Norse 10-12th centuries CE
Y-DNA: R-YP4342
mtDNA: H4a1a4b

Sample: VK186 / Greenland KNK-[6]
Location: Ø64, Eastern Settlement, Greenland
Age: Early Norse 10-12th centuries CE
Y-DNA: I-Y79817
FTDNA Comment: Shares 3 SNPs with a man from Norway downstream of I-Y24625. New branch = I-Y79817
mtDNA: H1ao

Sample: VK190 / Greenland late-0996
Location: Ø149, Eastern Settlement, Greenland
Age: Late Norse 1360 CE
Y-DNA: I-FGC15543
FTDNA Comment: Splits I-FGC15561. Derived 11 ancestral for 6. New path = I-FGC15543>I-FGC15561
mtDNA: K1a-T195C!

Sample: VK201 / Orkney_Buckquoy, sk M12
Location: Buckquoy_Birsay, Orkney, Scotland, UK
Age: Viking 5-6th century CE
Y-DNA: I-B293
mtDNA: H3k1a

Sample: VK202 / Orkney_Buckquoy, sk 7B
Location: Buckquoy_Birsay, Orkney, Scotland, UK
Age: Viking 10th century CE
Y-DNA: R-A151
mtDNA: H1ai1

Sample: VK203 / Orkney_BY78, Ar. 1, sk 3
Location: Brough_Road_Birsay, Orkney, Scotland, UK
Age: Viking 10th century CE
Y-DNA: R-BY10450
FTDNA Comment: FT83323-
mtDNA: H4a1a1a1a1

Sample: VK204 / Orkney_Newark for Brothwell
Location: Newark_Deerness, Orkney, Scotland, UK
Age: Viking 10th century CE
Y-DNA: R-BY115469
mtDNA: H1m

Sample: VK205 / Orkney_Newark 68/12
Location: Newark_Deerness, Orkney, Scotland, UK
Age: Viking 10th century CE
Y-DNA: R-YP4345
mtDNA: H3

Sample: VK210 / Poland_Kraków-Zakrzówek gr. 24
Location: Kraków, Poland
Age: Medieval 11-13th centuries CE
Y-DNA: I-Z16971
mtDNA: H5e1a1

Sample: VK211 / Poland_Cedynia gr. 435
Location: Cedynia, Poland
Age: Medieval 11-13 centuries CE
Y-DNA: R-M269
mtDNA: W6

Sample: VK212 / Poland_Cedynia gr. 558
Location: Cedynia, Poland
Age: Viking 11-12th centuries CE
Y-DNA: R-CTS11962
mtDNA: H1-T152C!

Sample: VK215 / Denmark_Gerdrup-B; sk 1
Location: Gerdrup, Sealand, Denmark
Age: Viking 9th century CE
Y-DNA: R-M269
mtDNA: J1c2k

Sample: VK217 / Sweden_Ljungbacka
Location: Ljungbacka, Malmo, Sweden
Age: Viking 9-12th centuries CE
Y-DNA: R-L151
mtDNA: J1b1b1

Sample: VK218 / Russia_Ladoga_5680-4
Location: Ladoga, Russia
Age: Viking 10-12th centuries CE
Y-DNA: R-BY2848
mtDNA: H5

Sample: VK219 / Russia_Ladoga_5680-10
Location: Ladoga, Russia
Age: Viking 10-11th centuries CE
Y-DNA: I-Y22024
mtDNA: T2b6a

Sample: VK220 / Russia_Ladoga_5680-11
Location: Ladoga, Russia
Age: Viking 10-12th centuries CE
Y-DNA: I-FT253975
FTDNA Comment: CTS2208+, BY47171-, CTS7676-, Y20288-, BY69785-, FT253975+
mtDNA: J2b1a

Sample: VK221 / Russia_Ladoga_5757-14
Location: Ladoga, Russia
Age: Viking 9-10th centuries CE
Y-DNA: I-Y5473
mtDNA: K1d

Sample: VK223 / Russia_Gnezdovo 75-140
Location: Gnezdovo, Russia
Age: Viking 10-11th centuries CE
Y-DNA: I-BY67763
mtDNA: H13a1a1c

Sample: VK224 / Russia_Gnezdovo 78-249
Location: Gnezdovo, Russia
Age: Viking 10-11th centuries CE
Y-DNA: N-CTS2929
mtDNA: H7a1

Sample: VK225 / Iceland_A108
Location: Hofstadir, Iceland
Age: Viking 10-13th centuries CE
Y-DNA: R-BY92608
mtDNA: H3v-T16093C

Sample: VK232 / Gotland_Kopparsvik-240.65
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-Y16505
FTDNA Comment: Speculative placement – U106+, but U106 (C>T) in ancient samples can be misleading. LAV010, NA34, I7779, ble007, R55 and EDM124 are all non-R ancient samples that are U106+. More conservative placement is at R-P310
mtDNA: N1a1a1

Sample: VK234 / Faroe_2
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-FT381000
FTDNA Comment: Same split as VK25. They share one marker FT381000 (26352237 T>G)
mtDNA: H3a1a

Sample: VK237 / Faroe_15
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-S6355
mtDNA: J2a2c

Sample: VK238 / Faroe_4
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-YP396
mtDNA: H3a1a

Sample: VK239 / Faroe_5
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-M269
mtDNA: H5

Sample: VK242 / Faroe_3
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-S764
mtDNA: H3a1a

Sample: VK244 / Faroe_12
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-CTS4179
mtDNA: H2a2a2

Sample: VK245 / Faroe_16
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: R-BY202785
FTDNA Comment: Forms a branch with VK46 down of R-BY202785 (Z287). New branch = R-FT383000
mtDNA: H3a1

Sample: VK248 / Faroe_22
Location: Church2, Faroes
Age: Early modern 16-17th centuries CE
Y-DNA: I-M253
mtDNA: H49a

Sample: VK251 / Gotland_Kopparsvik-30.64
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-M459
mtDNA: U5b1e1

Sample: VK256 / UK_Dorset-3722
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: R-YP5718
mtDNA: H1c7

Sample: VK257 / UK_Dorset-3723
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: I-Y19934
mtDNA: H5a1c1a

Sample: VK258 / UK_Dorset-3733
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: R-YP1395
FTDNA Comment: Shares 5 SNPs with a man from Norway. Forms a new branch down of R-YP1395. New branch = R-PH420
mtDNA: K1a4a1

Sample: VK259 / UK_Dorset-3734
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: R-FT20255
FTDNA Comment: Both VK449 and VK259 share 3 SNPs with a man from Sweden. Forms a new branch down of R-FT20255 (Z18). New branch = R-FT22694
mtDNA: I2

Sample: VK260 / UK_Dorset-3735
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: Q-BY77336
mtDNA: H1e1a

Sample: VK261 / UK_Dorset-3736
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: R-BY64643
mtDNA: H52

Sample: VK262 / UK_Dorset-3739
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: I-FT347811
FTDNA Comment: Shares 2 SNPs with an American of unknown origins. Forms a new branch down of Y6908 (Z140). At the same time a new branch was discovered that groups this new Ancient/American branch with the established I-FT274828 branch. New ancient path = I-Y6908>I-FT273257>I-FT347811
mtDNA: J1c4

Sample: VK263 / UK_Dorset-3742
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: R-Z16372
mtDNA: K1a4d

Sample: VK264 / UK_Dorset-3744
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: R-BY30937
mtDNA: N1a1a1a2

Sample: VK267 / Sweden_Karda 21
Location: Karda, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: R-L23
mtDNA: T2b4b

Sample: VK268 / Sweden_Karda 22
Location: Karda, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: R-M269
mtDNA: K1c1

Sample: VK269 / Sweden_Karda 24
Location: Karda, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: R-M269
mtDNA: H1e1a

Sample: VK273 / Russia_Gnezdovo 77-255
Location: Gnezdovo, Russia
Age: Viking 10-11th centuries CE
Y-DNA: R-BY61747
mtDNA: U5a2a1b1

Sample: VK274 / Denmark_Kaargarden 391
Location: Kaagården, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: R-PH3519
mtDNA: T2b-T152C!

Sample: VK275 / Denmark_Kaargarden 217
Location: Kaagården, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: I-BY74743
mtDNA: H

Sample: VK279 / Denmark_Galgedil AXE
Location: Galgedil, Funen, Denmark
Age: Viking 10th century CE
Y-DNA: I-Y10639
mtDNA: I4a

Sample: VK280 / Denmark_Galgedil UO
Location: Galgedil, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: I-Y3713
mtDNA: H11a

Sample: VK281 / Denmark_Barse Grav A
Location: Bårse, Sealand, Denmark
Age: Viking 10th century CE
Y-DNA: I-FGC22153
FTDNA Comment: Splits I-Y5612 (P109). Derived for 8, ancestral for 2. New path = I-Y5612>I-Y5619
mtDNA: T2

Sample: VK282 / Denmark_Stengade I, LMR c195
Location: Stengade_I, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: R-CTS1211
mtDNA: H4a1a4b

Sample: VK286 / Denmark_Bogovej Grav BJ
Location: Bogøvej, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: R-S10708
mtDNA: J1c-C16261T

Sample: VK287 / Denmark_Kaargarden Grav BS
Location: Kaagården, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: R-S22676
mtDNA: T2b

Sample: VK289 / Denmark_Bodkergarden Grav H, sk 1
Location: Bødkergarden, Langeland, Denmark
Age: Viking 9th century CE
Y-DNA: R-U106
mtDNA: J2b1a

Sample: VK290 / Denmark_Kumle Hoje Grav O
Location: Kumle_høje, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: R-FT264183
FTDNA Comment: Shares at least 4 SNPs with a man from Sweden, forming a new branch downstream R-FT263905 (U106). New branch = R-FT264183. HG02545 remains at R-FT263905
mtDNA: I1a1

Sample: VK291 / Denmark_Bodkergarden Grav D, sk 1
Location: Bødkergarden, Langeland, Denmark
Age: Viking 9th century CE
Y-DNA: I-Y20861
mtDNA: U5a1a2b

Sample: VK292 / Denmark_Bogovej Grav A.D.
Location: Bogøvej, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: R-M417
mtDNA: J1c2c1

Sample: VK295 / Denmark_Hessum sk 1
Location: Hessum, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: I-Y4738
mtDNA: T1a1

Sample: VK296 / Denmark_Hundstrup Mose sk 1
Location: Hundstrup_Mose, Sealand, Denmark
Age: Early Viking 660-780 CE
Y-DNA: I-S7660
mtDNA: HV6

Sample: VK297 / Denmark_Hundstrup Mose sk 2
Location: Hundstrup_Mose, Sealand, Denmark
Age: Early Viking 670-830 CE
Y-DNA: I-Y4051
mtDNA: J1c2h

Sample: VK301 / Denmark_Ladby Grav 4
Location: Ladby, Funen, Denmark
Age: Viking 640-890 CE
Y-DNA: I-FT105192
mtDNA: R0a2b

Sample: VK306 / Sweden_Skara 33
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: I-FT115400
FTDNA Comment: Shares 3 mutations with a man from Sweden. Forms a new branch down of I-S19291. New branch = I-FT115400. VK151 has no coverage for 2 of these mutations
mtDNA: H15a1

Sample: VK308 / Sweden_Skara 101
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-BY33037
mtDNA: H1c

Sample: VK309 / Sweden_Skara 53
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-YP6189
mtDNA: K1b1c

Sample: VK313 / Denmark_Rantzausminde Grav 2
Location: Rantzausminde, Funen, Denmark
Age: Viking 850-900 CE
Y-DNA: R-JFS0009
mtDNA: H1b

Sample: VK315 / Denmark_Bakkendrup Grav 16
Location: Bakkendrup, Sealand, Denmark
Age: Viking 850-900 CE
Y-DNA: I-Y98280
FTDNA Comment: Shares 1 SNP with a man from the Netherlands. Forms a new branch downstream of I-Y37415 (P109). New branch = I-Y98280
mtDNA: T1a1b

Sample: VK316 / Denmark_Hessum sk II
Location: Hessum, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: I-Y130659
FTDNA Comment: Splits I-Y130594 (Z59). Derived for 1 ancestral for 6. New path = I-Y130659>I-Y130594>I-Y130747. Ancient sample STR_486 also belongs in this group, at I-Y130747
mtDNA: K1a4

Sample: VK317 / Denmark_Kaargarden Grav BF99
Location: Kaagården, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: J-BY62479
FTDNA Comment: Splits J2-BY62479 (M67). Derived for 9, ancestral for 3. New path = J-BY62479>J-BY72550
mtDNA: H2a2a1

Sample: VK320 / Denmark_Bogovej Grav S
Location: Bogøvej, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: I-Y103013
FTDNA Comment: Shares 3 SNPs with a man from Sweden. Forms a new branch down of I-FT3562 (P109). New branch = I-Y103013
mtDNA: U5a1a1

Sample: VK323 / Denmark_Ribe 2
Location: Ribe, Jutland, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: R-S10185
mtDNA: K2a6

Sample: VK324 / Denmark_Ribe 3
Location: Ribe, Jutland, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: R-BY16590
FTDNA Comment: Splits R-BY16590 (L47). Derived for 7, ancestral for 3. New path = R-S9742>R-BY16950
mtDNA: N1a1a1a2

Sample: VK326 / Denmark_Ribe 5
Location: Ribe, Jutland, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: R-Y52895
mtDNA: U5b1-T16189C!-T16192C!

Sample: VK327 / Denmark_Ribe 6
Location: Ribe, Jutland, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: I-BY463
mtDNA: H6a1a5

Sample: VK329 / Denmark_Ribe 8
Location: Ribe, Jutland, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: R-S18894
mtDNA: H3-T152C!

Sample: VK332 / Oland_1088
Location: Oland, Sweden
Age: Viking 858 ±68 CE
Y-DNA: I-S8522
FTDNA Comment: Possibly falls beneath I-BY195155. Shares one C>T mutation with a BY195155* sample
mtDNA: T2b24

Sample: VK333 / Oland_1028
Location: Oland, Sweden
Age: Viking 885 ± 69 CE
Y-DNA: R-Z29034
mtDNA: H2a2a1

Sample: VK335 / Oland_1068
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: R-BY39347
FTDNA Comment: Shares 8 SNPs with a man from France. Forms a new branch down of R-BY39347 (U152). New branch = R-FT304388
mtDNA: K1b2a3

Sample: VK336 / Oland_1075
Location: Oland, Sweden
Age: Viking 853 ± 67 CE
Y-DNA: R-BY106906
mtDNA: K2a3a

Sample: VK337 / Oland_1064
Location: Oland, Sweden
Age: Viking 858 ± 68 CE
Y-DNA: I-BY31739
FTDNA Comment: Possible Z140
mtDNA: U5a1b3a

Sample: VK338 / Denmark_Bogovej Grav BV
Location: Bogøvej, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: R-A6707
mtDNA: W3a1

Sample: VK342 / Oland_1016
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: I-BY78615
FTDNA Comment: Shares 2 SNPs with a man from Finland. Forms a new branch down of I2-Y23710 (L801). New branch = I-BY78615
mtDNA: H2a1

Sample: VK343 / Oland_1021
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: I-Y7232
mtDNA: H3h

Sample: VK344 / Oland_1030
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: R-BY32357
mtDNA: J1c2t

Sample: VK345 / Oland_1045
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: R-FT148754
FTDNA Comment: Splits R-FT148754 (DF63). Derived for 8, ancestral for 6. New path = R-FT148796>R-FT148754
mtDNA: H4a1

Sample: VK346 / Oland_1057
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: J-Z8424
mtDNA: H2a2b

Sample: VK348 / Oland_1067
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: I-Z171
mtDNA: T2b28

Sample: VK349 / Oland_1073
Location: Oland, Sweden
Age: Viking 829 ± 57 CE
Y-DNA: R-BY166065
FTDNA Comment: Shares 2 SNPs with a man from England. Forms a branch down of R-BY166065 (L1066). New branch = R-BY167052
mtDNA: H1e2a

Sample: VK352 / Oland_1012
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: I-FGC35755
FTDNA Comment: Possibly forms a branch down of I-Y15295. 2 possible G>A mutations with a I-Y15295* sample
mtDNA: H64

Sample: VK354 / Oland_1026
Location: Oland, Sweden
Age: Viking 986 ± 38 CE
Y-DNA: R-S6752
mtDNA: H2a1

Sample: VK355 / Oland_1046
Location: Oland, Sweden
Age: Viking 847 ± 65 CE
Y-DNA: L-L595
FTDNA Comment: Joins 2 other ancients on this rare branch. ASH087 and I2923
mtDNA: U5b1b1a

Sample: VK357 / Oland_1097
Location: Oland, Sweden
Age: Viking 1053 ± 60 CE
Y-DNA: I-FT49567
FTDNA Comment: Shares 4 SNPs with a man from England. Forms a new branch down of I-A5952 (Z140). New branch = I-FT49567
mtDNA: J2b1a

Sample: VK362 / Denmark_Bogovej LMR 12077
Location: Bogøvej, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: E-CTS5856
FTDNA Comment: Possibly E-Z16663
mtDNA: V7b

Sample: VK363 / Denmark_Bogovej BT
Location: Bogøvej, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: I-BY198083
FTDNA Comment: Shares 2 SNPs with a man from Switzerland. Forms a new branch down of I-A1472 (Z140). New branch = I-BY198083
mtDNA: U4b1a1a1

Sample: VK365 / Denmark_Bogovej BS
Location: Bogøvej, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: R-BY34800
mtDNA: U8a2

Sample: VK367 / Denmark_Bogovej D
Location: Bogøvej, Langeland, Denmark
Age: Viking 10th century CE
Y-DNA: I-BY67827
FTDNA Comment: VK506 and VK367 split the I-BY67827 branch. Derived for 2 SNPs total. They also share one unique marker (26514336 G>C). New branches = I-Y16449>I-BY72774>I-FT382000
mtDNA: J1b1a1

Sample: VK369 / Denmark_Bakkendrup losfund-2, conc.1
Location: Bakkendrup, Sealand, Denmark
Age: Viking 850-900 CE
Y-DNA: R-FGC7556
FTDNA Comment: Shares 13 SNPs with an American. Forms a new branch down of R-FGC7556 (DF99). New branch = R-FT108043
mtDNA: H1a

Sample: VK373 / Denmark_Galgedil BER
Location: Galgedil, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: R-L20
mtDNA: J2b1a

Sample: VK379 / Oland_1077
Location: Oland, Sweden
Age: Early Viking 700 CE
Y-DNA: I-FGC22048
mtDNA: U3b1b

Sample: VK380 / Oland_1078
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: I-Y22923
mtDNA: H27

Sample: VK382 / Oland_1132
Location: Oland, Sweden
Age: Early Viking 700 CE
Y-DNA: I-L813
mtDNA: H3g1

Sample: VK384 / Denmark_Hesselbjerg Grav 14, sk EU
Location: Hesselbjerg, Jutland, Denmark
Age: Viking 850-900 CE
Y-DNA: R-FGC10249
mtDNA: H3g1

Sample: VK386 / Norway_Oppland 5305
Location: Oppland, Nor_South, Norway
Age: Viking 9-11th centuries CE
Y-DNA: R-S695
mtDNA: J1b1a1

Sample: VK388 / Norway_Nordland 253
Location: Nordland, Nor_North, Norway
Age: Viking 8-16th centuries CE
Y-DNA: I-Y22507
FTDNA Comment: Splits I-Y22507. Derived for 1 ancestral for 5. New path = I-Y22504>I-Y22507
mtDNA: J1c5

Sample: VK389 / Norway_Telemark 3697
Location: Telemark, Nor_South, Norway
Age: Viking 10th century CE
Y-DNA: R-Z27210
FTDNA Comment: Splits R-Z27210 (U106). Derived for 1 ancestral for 2. New path = R-Y32857>R-Z27210
mtDNA: T2b

Sample: VK390 / Norway_Telemark 1648-A
Location: Telemark, Nor_South, Norway
Age: Iron Age 5-6th centuries CE
Y-DNA: R-FT7019
mtDNA: K2a3

Sample: VK394 / Norway_Hedmark 4460
Location: Hedmark, Nor_South, Norway
Age: Viking 10th century CE
Y-DNA: R-YP5161
FTDNA Comment: Shares 1 SNP with a man from Denmark. Forms a new branch down of R-YP5161 (L448). New branch = R-BY186623
mtDNA: H13a1a1a

Sample: VK395 / Sweden_Skara 275
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: N-BY21973
mtDNA: X2c1

Sample: VK396 / Sweden_Skara 166
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-BY18970
FTDNA Comment: Splits R-BY18970 (DF98). Derived for 2, ancestral for 4 (BY18964+?). New path = R-BY18973>R-BY18970
mtDNA: J1c2t

Sample: VK397 / Sweden_Skara 237
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-S7759
mtDNA: J1b1a1

Sample: VK398 / Sweden_Skara 231
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: T-BY215080
mtDNA: H1b1-T16362C

Sample: VK399 / Sweden_Skara 276
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: N-FGC14542
mtDNA: H4a1a1a

Sample: VK400 / Sweden_Skara 236
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: I-FGC21682
mtDNA: H1-C16239T

Sample: VK401 / Sweden_Skara 229
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-YP5155
FTDNA Comment: Splits R-YP5155. Derived for 4, ancestral for 1. New path = R-YP5155>R-Y29963
mtDNA: H2a2b

Sample: VK403 / Sweden_Skara 217
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-BY3222
mtDNA: K1a4a1a2b

Sample: VK404 / Sweden_Skara 277
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: I-BY55382
FTDNA Comment: Shares 3 SNPs with a man from Sweden. Forms a new branch down of I-BY55382 (L22). New branch = I-BY108664
mtDNA: U4a2

Sample: VK405 / Sweden_Skara 83
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-L21
mtDNA: K1a10

Sample: VK406 / Sweden_Skara 203
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: N-Y7795
FTDNA Comment: Shares 2 SNPs with a man from Sweden. Forms a new branch down of N-Y7795. New branch = N-FT381631
mtDNA: K1a4a1

Sample: VK407 / Sweden_Skara 274
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: I-Y18232
mtDNA: H1c21

Sample: VK408 / Russia_Ladoga_5757-18
Location: Ladoga, Russia
Age: Viking 10-12th centuries CE
Y-DNA: R-CTS11962
mtDNA: H74

Sample: VK409 / Russia_Ladoga_5680-14
Location: Ladoga, Russia
Age: Viking 10-12th centuries CE
Y-DNA: I-DF29
mtDNA: H3h

Sample: VK410 / Russia_Ladoga_5680-15
Location: Ladoga, Russia
Age: Viking 11-12th centuries CE
Y-DNA: I-M253
mtDNA: X2b-T226C

Sample: VK411 / Denmark_Galgedil TT
Location: Galgedil, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: R-M269
mtDNA: H1a1

Sample: VK414 / Norway_Oppland 1517
Location: Oppland, Nor_South, Norway
Age: Viking 10-11th centuries CE
Y-DNA: R-PH12
FTDNA Comment: Splits R1a-PH12. Derived for 2, ancestral for 1. New path R-Y66214>R-PH12
mtDNA: H6a1a

Sample: VK418 / Norway_Nordland 1502
Location: Nordland, Nor_North, Norway
Age: Iron Age 4th century CE
Y-DNA: R-CTS5533
mtDNA: J1c2c1

Sample: VK419 / Norway_Nordland 1522
Location: Nordland, Nor_North, Norway
Age: Viking 6-10th centuries CE
Y-DNA: N-S9378
FTDNA Comment: Shares 2 SNPs with a man from France. Forms a new branch down of N-S9378 (L550). New branch = N-BY160234
mtDNA: U5b1b1g1

Sample: VK420 / Norway_Hedmark 2813
Location: Hedmark, Nor_South, Norway
Age: Viking 8-11th centuries CE
Y-DNA: I-FGC15560
FTDNA Comment: Shares 8 SNPs with an American man. Forms a new branch down of I-BY158446. New branch = I-FT118954
mtDNA: I4a

Sample: VK421 / Norway_Oppland 3777
Location: Oppland, Nor_South, Norway
Age: Viking 10-11th centuries CE
Y-DNA: R-M198
mtDNA: U5b2c2b

Sample: VK422 / Norway_Hedmark 4304
Location: Hedmark, Nor_South, Norway
Age: Viking 10th century CE
Y-DNA: R-YP390
mtDNA: J1b1a1a

Sample: VK424 / Sweden_Skara 273
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-M269
mtDNA: K2b1a1

Sample: VK425 / Sweden_Skara 44
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-Z331
mtDNA: U3a1

Sample: VK426 / Sweden_Skara 216
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: R-M269
mtDNA: U6a1a1

Sample: VK427 / Sweden_Skara 209
Location: Varnhem, Skara, Sweden
Age: Viking 10-12th centuries CE
Y-DNA: I-Y5362
mtDNA: K1a4

Sample: VK430 / Gotland_Frojel-00502
Location: Frojel, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: N-S18447
mtDNA: T1a1b

Sample: VK431 / Gotland_Frojel-00487A
Location: Frojel, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-P312
mtDNA: H2a1

Sample: VK438 / Gotland_Frojel-04498
Location: Frojel, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-CTS11962
mtDNA: H1

Sample: VK443 / Oland_1101
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: I-A20404
mtDNA: U5b2b5

Sample: VK444 / Oland_1059
Location: Oland, Sweden
Age: Viking 847 ± 65 CE
Y-DNA: R-PH1477
mtDNA: K1a

Sample: VK445 / Denmark_Gl Lejre-A1896
Location: Gl._Lejre, Sealand, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: I-Z2040
mtDNA: U3b

Sample: VK446 / Denmark_Galgedil LS
Location: Galgedil, Funen, Denmark
Age: Viking 9-11th centuries CE
Y-DNA: I-BY19383
FTDNA Comment: Shares 1 SNP with a man from England. Forms a new branch down of I-BY19383 (Z2041). New branch = I-BY94803
mtDNA: U5a1a1-T16362C

Sample: VK449 / UK_Dorset-3746
Location: Ridgeway_Hill_Mass_Grave_Dorset, Dorset, England, UK
Age: Viking 10-11th centuries CE
Y-DNA: R-FT20255
FTDNA Comment: Both VK449 and VK259 share 3 SNPs with a man from Sweden. Forms a new branch down of R-FT20255 (Z18). New branch = R-FT22694
mtDNA: H6a2a

Sample: VK452 / Gotland_Kopparsvik-111
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-CTS11962
mtDNA: T2b

Sample: VK453 / Gotland_Kopparsvik-134
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-YP256
mtDNA: H8c

Sample: VK461 / Gotland_Frojel-025A89
Location: Frojel, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: N-Y5005
FTDNA Comment: Possibly down of Y15161. Shares 2 C>T mutations with a Y15161* kit
mtDNA: H7b

Sample: VK463 / Gotland_Frojel-019A89
Location: Frojel, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-Y13467
mtDNA: H1b5

Sample: VK466 / Russia_Gnezdovo 77-222
Location: Gnezdovo, Russia
Age: Viking 10-11th centuries CE
Y-DNA: R-PF6162
mtDNA: H6a1a4

Sample: VK468 / Gotland_Kopparsvik-235
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-BY125166
mtDNA: H1a1

Sample: VK469 / Gotland_Kopparsvik-260
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-FGC17230
mtDNA: H3ac

Sample: VK471 / Gotland_Kopparsvik-63
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-M417
mtDNA: H1m

Sample: VK473 / Gotland_Kopparsvik-126
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: I-S14887
mtDNA: N1a1a1a1

Sample: VK474 / Gotland_Kopparsvik-137
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: E-Y4971
FTDNA Comment: Possible E-Y4972 (Shares 1 G>A mutation with a E-Y4972* sample)
mtDNA: J1d

Sample: VK475 / Gotland_Kopparsvik-187
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: R-BY27605
mtDNA: H1a

Sample: VK479 / Gotland_Kopparsvik-272
Location: Kopparsvik, Gotland, Sweden
Age: Viking 900-1050 CE
Y-DNA: G-Y106451
mtDNA: H1a1

Sample: VK480 / Estonia_Salme_II-E
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: R-YP617
mtDNA: U4a2a1

Sample: VK481 / Estonia_Salme_II-F
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: N-FGC14542
FTDNA Comment: Shares 1 SNP with a man from Sweden. Forms a new branch down of N-FGC14542. New branch = N–BY149019. VK399 possibly groups with these two as well
mtDNA: T2a1a

Sample: VK482 / Estonia_Salme_II-P
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-SK1234
mtDNA: H1a

Sample: VK483 / Estonia_Salme_II-V
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-Y141089
FTDNA Comment: Said to be brother of VK497 at I-BY86407 which is compatible with this placement, although no further Y-SNP evidence exists due to low coverage
mtDNA: H16

Sample: VK484 / Estonia_Salme_II-Q
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: R-FT103482
FTDNA Comment: VK484 and VK486 both split R-FT103482 (Z283). Derived for 9 ancestral for 6. New path = R-FT104609>R-FT103482
mtDNA: H6a1a

Sample: VK485 / Estonia_Salme_II-O
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-BY266
FTDNA Comment: Said to be brother of VK497 at I-BY86407 which is compatible with this placement, although no further Y-SNP evidence exists due to low coverage
mtDNA: H16

Sample: VK486 / Estonia_Salme_II-G
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: R-FT103482
FTDNA Comment: VK484 and VK486 both split R-FT103482 (Z283). Derived for 9 ancestral for 6. New path = R-FT104609>R-FT103482
mtDNA: U4a2a

Sample: VK487 / Estonia_Salme_II-A
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: R-YP4932
FTDNA Comment: Joins ancient Estonian samples V9 and X14
mtDNA: H17a2

Sample: VK488 / Estonia_Salme_II-H
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-L813
mtDNA: H5c

Sample: VK489 / Estonia_Salme_II-Ä
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: N-Y21546
mtDNA: T2e1

Sample: VK490 / Estonia_Salme_II-N
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-FGC8677
FTDNA Comment: Said to be brother of VK497 at I-BY86407 which is compatible with this placement, although no further Y-SNP evidence exists due to low coverage
mtDNA: H16

Sample: VK491 / Estonia_Salme_II-Õ
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-Y141089
mtDNA: H6a1a

Sample: VK492 / Estonia_Salme_II-B
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-Z73
mtDNA: H1b5

Sample: VK493 / Estonia_Salme_II-Š
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: R-S6353
FTDNA Comment: Shares 1 SNP with a man from Finland. Forms a new branch down of R-S6353. New branch = R-BY166432
mtDNA: H2a2a1

Sample: VK494 / Poland_Sandomierz 1/13
Location: Sandomierz, Poland
Age: Viking 10-11th centuries CE
Y-DNA: R-BY25698
mtDNA: X2c2

Sample: VK495 / Estonia_Salme_II-C
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-BY98617
FTDNA Comment: Shares 1 SNP with a man from Romania. Forms a branch down of I-BY98617 (L22). New branch = I-FT373923
mtDNA: H1b

Sample: VK496 / Estonia_Salme_II-W
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-BY198216
mtDNA: H1a

Sample: VK497 / Estonia_Salme_II-Ö
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-BY86407
mtDNA: H16

Sample: VK498 / Estonia_Salme_II-Z
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: R-S6752
mtDNA: H1q

Sample: VK504 / Estonia_Salme_I-1
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: N-S23232
mtDNA: H28a

Sample: VK505 / Estonia_Salme_I-2
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: N-Y30126
mtDNA: J1b1a1b

Sample: VK506 / Estonia_Salme_I-3
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-BY67827
FTDNA Comment: VK506 and VK367 split the I-BY67827 branch. Derived for 2 SNPs total. They also share one unique marker (26514336 G>C). New branches = I-Y16449>I-BY72774>I-FT382000
mtDNA: J1c2

Sample: VK507 / Estonia_Salme_I-4
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-CTS8407
FTDNA Comment: Shares 1 SNP with a man from Denmark. Forms a branch down of I-CTS8407 (P109). New branch = I-BY56459
mtDNA: HV6

Sample: VK508 / Estonia_Salme_I-5
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: N-Y10933
mtDNA: J1c5

Sample: VK509 / Estonia_Salme_I-6
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-Y36105
mtDNA: H1n-T146C!

Sample: VK510 / Estonia_Salme_I-7
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-Y19932
FTDNA Comment: Shares 8 SNPs with a man from Russia. Creates a new branch down of I-Y19932 (L22). New branch = I-BY60851
mtDNA: H10e

Sample: VK511 / Estonia_Salme_II-X
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-Y132154
mtDNA: T2a1a

Sample: VK512 / Estonia_Salme_II-Ü
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: N-Y21546
mtDNA: H2a2b1

Sample: VK513 / Greenland F8
Location: Ø029, East_Settlement, Greenland
Age: Early Norse 10-12th centuries CE
Y-DNA: R-S2886
mtDNA: J1c1b

Sample: VK514 / Norway_Nordland 5195
Location: Nordland, Nor_North, Norway
Age: Viking 6-10th centuries CE
Y-DNA: R-YP4963
mtDNA: K2b1a1

Sample: VK515 / Norway_Nordland 4512
Location: Nordland, Nor_North, Norway
Age: Viking 10th century CE
Y-DNA: I-FGC8677
mtDNA: H52

Sample: VK516 / Norway_Sor-Trondelag 4481
Location: Sor-Trondelag, Nor_Mid, Norway
Age: Viking 10th century CE
Y-DNA: R-CTS8746
mtDNA: H6a1a

Sample: VK517 / Sweden_Uppsala_UM36031_623b
Location: Skämsta, Uppsala, Sweden
Age: Viking 11th century
Y-DNA: I-BY78615
mtDNA: J1c3f

Sample: VK519 / Norway_Nordland 4691b
Location: Nordland, Nor_North, Norway
Age: Viking 6-10th centuries CE
Y-DNA: I-M253
mtDNA: HV0a1

Sample: VK521 / Sol941 Grav900 Brondsager Torsiinre
Location: Brondsager_Torsiinre, Sealand, Denmark
Age: Iron Age 300 CE
Y-DNA: I-FGC43065
mtDNA: H16b

Sample: VK524 / Norway_Nordland 3708
Location: Nordland, Nor_North, Norway
Age: Viking 10th century CE
Y-DNA: I-M6155
mtDNA: HV0a1

Sample: VK528 / Norway_Troms 4049
Location: Troms, Nor_North, Norway
Age: Viking 8-9th centuries CE
Y-DNA: R-BY135243
mtDNA: K1a4a1b

Sample: VK529 / Norway_Nordland 642
Location: Nordland, Nor_North, Norway
Age: Viking 8-9th centuries CE
Y-DNA: I-BY106963
mtDNA: H7

Sample: VK531 / Norway_Troms 5001A
Location: Troms, Nor_North, Norway
Age: LNBA 2400 BC
Y-DNA: R-Y13202
mtDNA: U2e2a

Sample: VK532 / Kragehave Odetofter XL718
Location: Kragehave Odetofter, Sealand, Denmark
Age: Iron Age 100 CE
Y-DNA: I-S26361
FTDNA Comment: Shares 5 SNPs with a man from Sweden. Forms a new branch down of I-S26361 (Z2041). New branch = I-FT273387
mtDNA: U2e2a1a

Sample: VK533 / Oland 1076 28364 35
Location: Oland, Sweden
Age: Viking 9-11th centuries CE
Y-DNA: N-BY21933
FTDNA Comment: Splits N-BY21933 (L550). Derived for 1 ancestral for 13. New path = N-BY29005>N-BY21933
mtDNA: H13a1a1e

Sample: VK534 / Italy_Foggia-869
Location: San_Lorenzo, Foggia, Italy
Age: Medieval 11-13th centuries CE
Y-DNA: R-FGC71023
mtDNA: H1

Sample: VK535 / Italy_Foggia-891
Location: San_Lorenzo, Foggia, Italy
Age: Medieval 12-13th centuries CE
Y-DNA: R-Z2109
mtDNA: T1a5

Sample: VK538 / Italy_Foggia-1249
Location: Cancarro, Foggia, Italy
Age: Medieval 11-13th centuries CE
Y-DNA: L-Z5931
mtDNA: H-C16291T

Sample: VK539 / Ukraine_Shestovitsa-8870-97
Location: Shestovitsa, Ukraine
Age: Viking 10-12th centuries CE
Y-DNA: I-BY61100
FTDNA Comment: Splits I-BY61100 (Z2041). Derived for 5 ancestral for 3. New path I-BY65928>I-BY61100
mtDNA: V

Sample: VK541 / Ukraine_Lutsk
Location: Lutsk, Ukraine
Age: Medieval 13th century
Y-DNA: R-YP593
mtDNA: H7

Sample: VK542 / Ukraine_Chernigov
Location: Chernigov, Ukraine
Age: Viking 11th century
Y-DNA: I-S20602
mtDNA: H5a2a

Sample: VK543 / Ireland_EP55
Location: Eyrephort, Ireland
Age: Viking 9th century CE
Y-DNA: R-S2895
mtDNA: I2

Sample: VK545 / Ireland_SSG12
Location: Ship_Street_Great, Dublin, Ireland
Age: Viking 7-9th centuries CE
Y-DNA: R-DF105
mtDNA: H1bb

Sample: VK546 / Ireland_08E693
Location: Islandbridge, Dublin, Ireland
Age: Viking 9th century CE
Y-DNA: R-L448
mtDNA: HV6

Sample: VK547 / Norway_Nordland 4727
Location: Nordland, Nor_North, Norway
Age: Viking 8-11th centuries CE
Y-DNA: I-FT8660
FTDNA Comment: Splits I-FT8660 (L813) Derived for 3, ancestral for 3. New path = I-FT8660>I-FT8457
mtDNA: V

Sample: VK549 / Estonia_Salme_II-J
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-P109
mtDNA: T2b5a

Sample: VK550 / Estonia_Salme_II-D
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: N-Y4706
mtDNA: V

Sample: VK551 / Estonia_Salme_II-U
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: R-CTS4179
mtDNA: J2a1a1a2

Sample: VK552 / Estonia_Salme_II-K
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-Z2900
mtDNA: H10e

Sample: VK553 / Estonia_Salme_II-M
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-FGC22026
FTDNA Comment: Splits I-FGC22026. Derived for 1, ancestral for 7. New path = I-FGC22035>I-FGC22026
mtDNA: K1c1h

Sample: VK554 / Estonia_Salme_II-L
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-M253
mtDNA: W6a

Sample: VK555 / Estonia_Salme_II-I
Location: Salme, Saaremaa, Estonia
Age: Early Viking 8th century CE
Y-DNA: I-Z73
mtDNA: U3b1b

Sample: VK579 / Oland 1099 1785/67 35
Location: Oland, Sweden
Age: Iron Age 200-400 CE
Y-DNA: N-L550
mtDNA: H1s

Sample: VK582 / SBM1028 ALKEN ENGE 2013, X2244
Location: Alken_Enge, Jutland, Denmark
Age: Iron Age 1st century CE
Y-DNA: I-L801
mtDNA: H6a1b3

Update History:

  • 9-17-2020 – updated 3 times, approximately one-third complete
  • 9-18-2020 – updated in afternoon with another 124 analyzed
  • 9-19-2020 – updated with 142 analyzed
  • 9-21-2020 – updates with 240 analyzed – only 60 to go!
  • 9-22-2020 – last update – A total of 285 entries analyzed and placed on the FTDNA tree where appropriate. 15 were too low quality or low coverage for a reliable haplogroup call, so they were excluded.

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Y DNA: Step-by-Step Big Y Analysis

Many males take the Big Y-700 test offered by FamilyTreeDNA, so named because testers receive the most granular haplogroup SNP results in addition to 700+ included STR marker results. If you’re not familiar with those terms, you might enjoy the article, STRs vs SNPs, Multiple DNA Personalities.

The Big Y test gives testers the best of both, along with contributing to the building of the Y phylotree. You can read about the additions to the Y tree via the Big Y, plus how it helped my own Estes project, here.

Some men order this test of their own volition, some at the request of a family member, and some in response to project administrators who are studying a specific topic – like a particular surname.

The Big Y-700 test is the most complete Y DNA test offered, testing millions of locations on the Y chromosome to reveal mutations, some unique and never before discovered, many of which are useful to genealogists. The Big Y-700 includes the traditional Y DNA STR marker testing along with SNP results that define haplogroups. Translated, both types of test results are compared to other men for genealogy, which is the primary goal of DNA testing.

Being a female, I often recruit males in my family surname lines and sponsor testing. My McNiel line, historic haplogroup R-M222, has been particularly frustrating both genealogically as well as genetically after hitting a brick wall in the 1700s. My McNeill cousin agreed to take a Big Y test, and this analysis walks through the process of understanding what those results are revealing.

After my McNeill cousin’s Big Y results came back from the lab, I spent a significant amount of time turning over every leaf to extract as much information as possible, both from the Big Y-700 DNA test itself and as part of a broader set of intertwined genetic information and genealogical evidence.

I invite you along on this journey as I explain the questions we hoped to answer and then evaluate Big Y DNA results along with other information to shed light on those quandaries.

I will warn you, this article is long because it’s a step-by-step instruction manual for you to follow when interpreting your own Big Y results. I’d suggest you simply read this article the first time to get a feel for the landscape, before working through the process with your own results. There’s so much available that most people leave laying on the table because they don’t understand how to extract the full potential of these test results.

If you’d like to read more about the Big Y-700 test, the FamilyTreeDNA white paper is here, and I wrote about the Big Y-700 when it was introduced, here.

You can read an overview of Y DNA, here, and Y DNA: The Dictionary of DNA, here.

Ok, get yourself a cuppa joe, settle in, and let’s go!

George and Thomas McNiel – Who Were They?

George and Thomas McNiel appear together in Spotsylvania County, Virginia records. Y DNA results, in combination with early records, suggest that these two men were brothers.

I wrote about discovering that Thomas McNeil’s descendant had taken a Y DNA test and matched George’s descendants, here, and about my ancestor George McNiel, here.

McNiel family history in Wilkes County, NC, recorded in a letter written in 1898 by George McNiel’s grandson tells us that George McNiel, born about 1720, came from Scotland with his two brothers, John and Thomas. Elsewhere, it was reported that the McNiel brothers sailed from Glasgow, Scotland and that George had been educated at the University of Edinburgh for the Presbyterian ministry but had a change of religious conviction during the voyage. As a result, a theological tiff developed that split the brothers.

George, eventually, if not immediately, became a Baptist preacher. His origins remain uncertain.

The brothers reportedly arrived about 1750 in Maryland, although I have no confirmation. By 1754, Thomas McNeil appeared in the Spotsylvania County, VA records with a male being apprenticed to him as a tailor. In 1757, in Spotsylvania County, the first record of George McNeil showed James Pey being apprenticed to learn the occupation of tailor.

If George and Thomas were indeed tailors, that’s not generally a country occupation and would imply that they both apprenticed as such when they were growing up, wherever that was.

Thomas McNeil is recorded in one Spotsylvania deed as being from King and Queen County, VA. If this is the case, and George and Thomas McNiel lived in King and Queen, at least for a time, this would explain the lack of early records, as King and Queen is a thrice-burned county. If there was a third brother, John, I find no record of him.

My now-deceased cousin, George McNiel, initially tested for the McNiel Y DNA and also functioned for decades as the family historian. George, along with his wife, inventoried the many cemeteries of Wilkes County, NC.

George believed through oral history that the family descended from the McNiel’s of Barra.

McNiel Big Y Kisumul

George had this lovely framed print of Kisimul Castle, seat of the McNiel Clan on the Isle of Barra, proudly displayed on his wall.

That myth was dispelled with the initial DNA testing when our line did not match the Barra line, as can be seen in the MacNeil DNA project, much to George’s disappointment. As George himself said, the McNiel history is both mysterious and contradictory. Amen to that, George!

McNiel Big Y Niall 9 Hostages

However, in place of that history, we were instead awarded the Niall of the 9 Hostages badge, created many years ago based on a 12 marker STR result profile. Additionally, the McNiel DNA was assigned to haplogroup R-M222. Of course, today’s that’s a far upstream haplogroup, but 15+ years ago, we had only a fraction of the testing or knowledge that we do today.

The name McNeil, McNiel, or however you spell it, resembles Niall, so on the surface, this made at least some sense. George was encouraged by the new information, even though he still grieved the loss of Kisimul Castle.

Of course, this also caused us to wonder about the story stating our line had originated in Scotland because Niall of the 9 Hostages lived in Ireland.

Niall of the 9 Hostages

Niall of the 9 Hostages was reportedly a High King of Ireland sometime between the 6th and 10th centuries. However, actual historical records place him living someplace in the mid-late 300s to early 400s, with his death reported in different sources as occurring before 382 and alternatively about 411. The Annals of the Four Masters dates his reign to 379-405, and Foras Feasa ar Eirinn says from 368-395. Activities of his sons are reported between 379 and 405.

In other words, Niall lived in Ireland about 1500-1600 years ago, give or take.

Migration

Generally, migration was primarily from Scotland to Ireland, not the reverse, at least as far as we know in recorded history. Many Scottish families settled in the Ulster Plantation beginning in 1606 in what is now Northern Ireland. The Scots-Irish immigration to the states had begun by 1718. Many Protestant Scottish families immigrated from Ireland carrying the traditional “Mc” names and Presbyterian religion, clearly indicating their Scottish heritage. The Irish were traditionally Catholic. George could have been one of these immigrants.

We have unresolved conflicts between the following pieces of McNeil history:

  • Descended from McNeil’s of Barra – disproved through original Y DNA testing.
  • Immigrated from Glasgow, Scotland, and schooled in the Presbyterian religion in Edinburgh.
  • Descended from the Ui Neill dynasty, an Irish royal family dominating the northern half of Ireland from the 6th to 10th centuries.

Of course, it’s possible that our McNiel/McNeil line could have been descended from the Ui Neill dynasty AND also lived in Scotland before immigrating.

It’s also possible that they immigrated from Ireland, not Scotland.

And finally, it’s possible that the McNeil surname and M222 descent are not related and those two things are independent and happenstance.

A New Y DNA Tester

Since cousin George is, sadly, deceased, we needed a new male Y DNA tester to represent our McNiel line. Fortunately, one such cousin graciously agreed to take the Big Y-700 test so that we might, hopefully, answer numerous questions:

  • Does the McNiel line have a unique haplogroup, and if so, what does it tell us?
  • Does our McNiel line descend from Ireland or Scotland?
  • Where are our closest geographic clusters?
  • What can we tell by tracing our haplogroup back in time?
  • Do any other men match the McNiel haplogroup, and what do we know about their history?
  • Does the Y DNA align with any specific clans, clan history, or prehistory contributing to clans?

With DNA, you don’t know what you don’t know until you test.

Welcome – New Haplogroup

I was excited to see my McNeill cousin’s results arrive. He had graciously allowed me access, so I eagerly took a look.

He had been assigned to haplogroup R-BY18350.

McNiel Big Y branch

Initially, I saw that indeed, six men matched my McNeill cousin, assigned to the same haplogroup. Those surnames were:

  • Scott
  • McCollum
  • Glass
  • McMichael
  • Murphy
  • Campbell

Notice that I said, “were.” That’s right, because shortly after the results were returned, based on markers called private variants, Family Tree DNA assigned a new haplogroup to my McNeill cousin.

Drum roll please!!!

Haplogroup R-BY18332

McNiel Big Y BY18332

Additionally, my cousin’s Big Y test resulted in several branches being split, shown on the Block Tree below.

McNIel Big Y block tree

How cool is this!

This Block Tree graphic shows, visually, that our McNiel line is closest to McCollum and Campbell testers, and is a brother clade to those branches showing to the left and right of our new R-BY18332. It’s worth noting that BY25938 is an equivalent SNP to BY18332, at least today. In the future, perhaps another tester will test, allowing those two branches to be further subdivided.

Furthermore, after the new branches were added, Cousin McNeill has no more Private Variants, which are unnamed SNPs. There were all utilized in naming additional tree branches!

I wrote about the Big Y Block Tree here.

Niall (Or Whoever) Was Prolific

The first thing that became immediately obvious was how successful our progenitor was.

McNiel Big Y M222 project

click to enlarge

In the MacNeil DNA project, 38 men with various surname spellings descend from M222. There are more in the database who haven’t joined the MacNeil project.

Whoever originally carried SNP R-M222, someplace between 2400 and 5900 years ago, according to the block tree, either had many sons who had sons, or his descendants did. One thing is for sure, his line certainly is in no jeopardy of dying out today.

The Haplogroup R-M222 DNA Project, which studies this particular haplogroup, reads like a who’s who of Irish surnames.

Big Y Match Results

Big Y matches must have no more than 30 SNP differences total, including private variants and named SNPs combined. Named SNPs function as haplogroup names. In other words, Cousin McNeill’s terminal SNP, meaning the SNP furthest down on the tree, R-BY18332, is also his haplogroup name.

Private variants are mutations that have occurred in the line being tested, but not yet in other lines. Occurrences of private variants in multiple testers allow the Private Variant to be named and placed on the haplotree.

Of course, Family Tree DNA offers two types of Y DNA testing, STR testing which is the traditional 12, 25, 37, 67 and 111 marker testing panels, and the Big Y-700 test which provides testers with:

  • All 111 STR markers used for matching and comparison
  • Another 589+ STR markers only available through the Big Y test increasing the total STR markers tested from 111 to minimally 700
  • A scan of the Y chromosome, looking for new and known SNPs and STR mutations

Of course, these tests keep on giving, both with matching and in the case of the Big Y – continued haplogroup discovery and refinement in the future as more testers test. The Big Y is an investment as a test that keeps on giving, not just a one-time purchase.

I wrote about the Big Y-700 when it was introduced here and a bit later here.

Let’s see what the results tell us. We’ll start by taking a look at the matches, the first place that most testers begin.

Mcniel Big Y STR menu

Regular Y DNA STR matching shows the results for the STR results through 111 markers. The Big Y section, below, provides results for the Big Y SNPs, Big Y matches and additional STR results above 111 markers.

McNiel Big Y menu

Let’s take a look.

STR and SNP Testing

Of Cousin McNeil’s matches, 2 Big Y testers and several STR testers carry some variant of the Neal, Neel, McNiel, McNeil, O’Neil, etc. surnames by many spellings.

While STR matching is focused primarily on a genealogical timeframe, meaning current to roughly 500-800 years in the past, SNP testing reaches much further back in time.

  • STR matching reaches approximately 500-800 years.
  • Big Y matching reaches approximately 1500 years.
  • SNPs and haplogroups reach back infinitely, and can be tracked historically beyond the genealogical timeframe, shedding light on our ancestors’ migration paths, helping to answer the age-old question of “where did we come from.”

These STR and Big Y time estimates are based on a maximum number of mutations for testers to be considered matches paired with known genealogy.

Big Y results consider two men a match if they have 30 or fewer total SNP differences. Using NGS (next generation sequencing) scan technology, the targeted regions of the Y chromosome are scanned multiple times, although not all regions are equally useful.

Individually tested SNPs are still occasionally available in some cases, but individual SNP testing has generally been eclipsed by the greatly more efficient enriched technology utilized with Big Y testing.

Think of SNP testing as walking up to a specific location and taking a look, while NGS scan technology is a drone flying over the entire region 30-50 times looking multiple times to be sure they see the more distant target accurately.

Multiple scans acquiring the same read in the same location, shown below in the Big Y browser tool by the pink mutations at the red arrow, confirm that NGS sequencing is quite reliable.

McNiel Big Y browser

These two types of tests, STR panels 12-111 and the SNP-based Big Y, are meant to be utilized in combination with each other.

STR markers tend to mutate faster and are less reliable, experiencing frustrating back mutations. SNPs very rarely experience this level of instability. Some regions of the Y chromosome are messier or more complicated than others, causing problems with interpreting reads reliably.

For purposes of clarity, the string of pink A reads above is “not messy,” and “A” is very clearly a mutation because all ~39 scanned reads report the same value of “A,” and according to the legend, all of those scans are high quality. Multiple combined reads of A and G, for example, in the same location, would be tough to call accurately and would be considered unreliable.

You can see examples of a few scattered pink misreads, above.

The two different kinds of tests produce results for overlapping timeframes – with STR mutations generally sifting through closer relationships and SNPs reaching back further in time.

Many more men have taken the Y DNA STR tests over the last 20 years. The Big Y tests have only been available for the past handful of years.

STR testing produces the following matches for my McNiel cousin:

STR Level STR Matches STR Matches Who Took the Big Y % STR Who Took Big Y STR Matches Who Also Match on the Big Y
12 5988 796 13 52
25 6660 725 11 57
37 878 94 11 12
67 1225 252 21 23
111 4 2 50 1

Typically, one would expect that all STR matches that took the Big Y would match on the Big Y, since STR results suggest relationships closer in time, but that’s not the case.

  • Many STR testers who have taken the Big Y seem to be just slightly too distant to be considered a Big Y match using SNPs, which flies in the face of conventional wisdom.
  • However, this could easily be a function of the fact that STRs mutate both backward and forwards and may have simply “happened” to have mutated to a common value – which suggests a closer relationship than actually exists.
  • It could also be that the SNP matching threshold needs to be raised since the enhanced and enriched Big Y-700 technology now finds more mutations than the older Big Y-500. I would like to see SNP matching expanded to 40 from 30 because it seems that clan connections may be being missed. Thirty may have been a great threshold before the more sensitive Big Y-700 test revealed more mutations, which means that people hit that 30 threshold before they did with previous tests.
  • Between the combination of STRs and SNPs mutating at the same time, some Big Y matches are pushed just out of range.

In a nutshell, the correlation I expected to find in terms of matching between STR and Big Y testing is not what I found. Let’s take a look at what we discovered.

It’s worth noting that the analysis is easier if you are working together with at least your closest matches or have access via projects to at least some of their results. You can see common STR values to 111 in projects, such as surname projects. Project administrators can view more if project members have allowed access.

Unexpected Discoveries and Gotchas

While I did expect STR matches to also match on the Big Y, I don’t expect the Big Y matches to necessarily match on the STR tests. After all, the Big Y is testing for more deep-rooted history.

Only one of the McNiel Big Y matches also matches at all levels of STR testing. That’s not surprising since Big Y matching reaches further back in time than STR testing, and indeed, not all STR testers have taken a Big Y test.

Of my McNeill cousin’s closest Big Y matches, we find the following relative to STR matching.

Surname Ancestral Location Big Y Variant/SNP Difference STR Match Level
Scott 1565 in Buccleuch, Selkirkshire, Scotland 20 12, 25, 37, 67
McCollum Not listed 21 67 only
Glass 1618 in Banbridge, County Down, Ireland 23 12, 25, 67
McMichael 1720 County Antrim, Ireland 28 67 only
Murphy Not listed 29 12, 25, 37, 67
Campbell Scotland 30 12, 25, 37, 67, 111

It’s ironic that the man who matches on all STR levels has the most variants, 30 – so many that with 1 more, he would not have been considered a Big Y match at all.

Only the Campbell man matches on all STR panels. Unfortunately, this Campbell male does not match the Clan Campbell line, so that momentary clan connection theory is immediately put to rest.

Block Tree Matches – What They Do, and Don’t, Mean

Note that a Carnes male, the other person who matches my McNeill cousin at 111 STR markers and has taken a Big Y test does not match at the Big Y level. His haplogroup BY69003 is located several branches up the tree, with our common ancestor, R-S588, having lived about 2000 years ago. Interestingly, we do match other R-S588 men.

This is an example where the total number of SNP mutations is greater than 30 for these 2 men (McNeill and Carnes), but not for my McNeill cousin compared with other men on the same S588 branch.

McNiel Big Y BY69003

By searching for Carnes on the block tree, I can view my cousin’s match to Mr. Carnes, even though they don’t match on the Big Y. STR matches who have taken the Big Y test, even if they don’t match at the Big Y level, are shown on the Block Tree on their branch.

By clicking on the haplogroup name, R-BY69003, above, I can then see three categories of information about the matches at that haplogroup level, below.

McNiel Big Y STR differences

click to enlarge

By selecting “Matches,” I can see results under the column, “Big Y.” This does NOT mean that the tester matches either Mr. Carnes or Mr. Riker on the Big Y, but is telling me that there are 14 differences out of 615 STR markers above 111 markers for Mr. Carnes, and 8 of 389 for Mr. Riker.

In other words, this Big Y column is providing STR information, not indicating a Big Y match. You can’t tell one way or another if someone shown on the Block Tree is shown there because they are a Big Y match or because they are an STR match that shares the same haplogroup.

As a cautionary note, your STR matches that have taken the Big Y ARE shown on the block tree, which is a good thing. Just don’t assume that means they are Big Y matches.

The 30 SNP threshold precludes some matches.

My research indicates that the people who match on STRs and carry the same haplogroup, but don’t match at the Big Y level, are every bit as relevant as those who do match on the Big Y.

McNIel Big Y block tree menu

If you’re not vigilant when viewing the block tree, you’ll make the assumption that you match all of the people showing on the Block Tree on the Big Y test since Block Tree appears under the Big Y tools. You have to check Big Y matches specifically to see if you match people shown on the Block Tree. You don’t necessarily match all of them on the Big Y test, and vice versa, of course.

You match Block Tree inhabitants either:

  • On the Big Y, but not the STR panels
  • On the Big Y AND at least one level of STRs between 12 and 111, inclusive
  • On STRs to someone who has taken the Big Y test, but whom you do not match on the Big Y test

Big Y-500 or Big Y-700?

McNiel Big Y STR differences

click to enlarge

Looking at the number of STR markers on the matches page of the Block Tree for BY69003, above, or on the STR Matches page is the only way to determine whether or not your match took the Big Y-700 or the Big Y-500 test.

If you add 111 to the Big Y SNP number of 615 for Mr. Carnes, the total equals 726, which is more than 700, so you know he took the Big Y-700.

If you add 111 to 389 for Mr. Riker, you get 500, which is less than 700, so you know that he took the Big Y-500 and not the Big Y-700.

There are still a very small number of men in the database who did not upgrade to 111 when they ordered their original Big Y test, but generally, this calculation methodology will work. Today, all Big Y tests are upgraded to 111 markers if they have not already tested at that level.

Why does Big Y-500 vs Big Y-700 matter? The enriched chemistry behind the testing technology improved significantly with the Big Y-700 test, enhancing Y-DNA results. I was an avowed skeptic until I saw the results myself after upgrading men in the Estes DNA project. In other words, if Big Y-500 testers upgrade, they will probably have more SNPs in common.

You may want to contact your closest Big Y-500 matches and ask if they will consider upgrading to the Big Y-700 test. For example, if we had close McNiel or similar surname matches, I would do exactly that.

Matching Both the Big Y and STRs – No Single Source

There is no single place or option to view whether or not you match someone BOTH on the Big Y AND STR markers. You can see both match categories individually, of course, but not together.

You can determine if your STR matches took the Big Y, below, and their haplogroup, which is quite useful, but you can’t tell if you match them at the Big Y level on this page.

McNiel Big Y STR match Big Y

click to enlarge

Selecting “Display Only Matches With Big Y” means displaying matches to men who took the Big Y test, not necessarily men you match on the Big Y. Mr. Conley, in the example above, does not match my McNeill cousin on the Big Y but does match him at 12 and 25 STR markers.

I hope FTDNA will add three display options:

  • Select only men that match on the Big Y in the STR panel
  • Add an option for Big Y on the advanced matches page
  • Indicate men who also match on STRs on the Big Y match page

It was cumbersome and frustrating to have to view all of the matches multiple times to compile various pieces of information in a separate spreadsheet.

No Big Y Match Download

There is also no option to download your Big Y matches. With a few matches, this doesn’t matter, but with 119 matches, or more, it does. As more people test, everyone will have more matches. That’s what we all want!

What you can do, however, is to download your STR matches from your match page at levels 12-111 individually, then combine them into one spreadsheet. (It would be nice to be able to download them all at once.)

McNiel Big Y csv

You can then add your Big Y matches manually to the STR spreadsheet, or you can simply create a separate Big Y spreadsheet. That’s what I chose to do after downloading my cousin’s 14,737 rows of STR matches. I told you that R-M222 was prolific! I wasn’t kidding.

This high number of STR matches also perfectly illustrates why the Big Y SNP results were so critical in establishing the backbone relationship structure. Using the two tools together is indispensable.

An additional benefit to downloading STR results is that you can sort the STR spreadsheet columns in surname order. This facilitates easily spotting all spelling variations of McNiel, including words like Niel, Neal and such that might be relevant but that you might not notice otherwise.

Creating a Big Y Spreadsheet

My McNiel cousin has 119 Big Y-700 matches.

I built a spreadsheet with the following columns facilitating sorting in a number of ways, with definitions as follows:

McNiel Big Y spreadsheet

click to enlarge

  • First Name
  • Last Name – You will want to search matches on your personal page at Family Tree DNA by this surname later, so be sure if there is a hyphenated name to enter it completely.
  • Haplogroup – You’ll want to sort by this field.
  • Convergent – A field you’ll complete when doing your analysis. Convergence is the common haplogroup in the tree shared by you and your match. In the case of the green matches above, which are color-coded on my spreadsheet to indicate the closest matches with my McNiel cousin, the convergent haplogroup is BY18350.
  • Common Tree Gen – This column is the generations on the Block Tree shown to this common haplogroup. In the example above, it’s between 9 and 14 SNP generations. I’ll show you where to gather this information.
  • Geographic Location – Can be garnered from 4 sources. No color in that cell indicates that this information came from the Earliest Known Ancestor (EKA) field in the STR matches. Blue indicates that I opened the tree and pulled the location information from that source. Orange means that someone else by the same surname whom the tester also Y DNA matches shows this location. I am very cautious when assigning orange, and it’s risky because it may not be accurate. A fourth source is to use Ancestry, MyHeritage, or another genealogical resource to identify a location if an individual provides genealogical information but no location in the EKA field. Utilizing genealogy databases is only possible if enough information is provided to make a unique identification. John Smith 1700-1750 won’t do it, but Seamus McDougal (1750-1810) married to Nelly Anderson might just work.
  • STR Match – Tells me if the Big Y match also matches on STR markers, and if so, which ones. Only the first 111 markers are used for matching. No STR match generally means the match is further back in time, but there are no hard and fast rules.
  • Big Y Match – My original goal was to combine this information with the STR match spreadsheet. If you don’t wish to combine the two, then you don’t need this column.
  • Tree – An easy way for me to keep track of which matches do and do not have a tree. Please upload or create a tree.

You can also add a spreadsheet column for comments or contact information.

McNiel Big Y profile

You will also want to click your match’s name to display their profile card, paying particular attention to the “About Me” information where people sometimes enter genealogical information. Also, scan the Ancestral Surnames where the match may enter a location for a specific surname.

Private Variants

I added additional spreadsheet columns, not shown above, for Private Variant analysis. That level of analysis is beyond what most people are interested in doing, so I’m only briefly discussing this aspect. You may want to read along, so you at least understand what you are looking at.

Clicking on Private Variants in your Big Y Results shows your variants, or mutations, that are unnamed as SNPs. When they are named, they become SNPs and are placed on the haplotree.

The reference or “normal” state for the DNA allele at that location is shown as the “Reference,” and “Genotype” is the result of the tester. Reference results are not shown for each tester, because the majority are the same. Only mutations are shown.

McNiel Big Y private variants

There are 5 Private Variants, total, for my cousin. I’ve obscured the actual variant numbers and instead typed in 111111 and 222222 for the first two as examples.

McNiel Big Y nonmatching variants

In our example, there are 6 Big Y matches, with matches one and five having the non-matching variants shown above.

Non-matching variants mean that the match, Mr. Scott, in example 1, does NOT match the tester (my cousin) on those variants.

  • If the tester (you) has no mutation, you won’t have a Private Variant shown on your Private Variant page.
  • If the tester does have a Private Variant shown, and that variant shows ON their matches list of non-matching variants, it means the match does NOT match the tester, and either has the normal reference value or a different mutation. Explained another way, if you have a mutation, and that variant is listed on your match list of Non-Matching Variants, your match does NOT match you and does NOT have the same mutation.
  • If the match does NOT have the Private Variant on their list, that means the match DOES match the tester, and they both have the same mutation, making this Private Variant a candidate to be named as a new SNP.
  • If you don’t have a Private Variant listed, but it shows in the Non-Matching Variants of your match, that means you have the reference or normal value, and they have a mutation.

In example #1, above, the tester has a mutation at variant 111111, and 111111 is shown as a Non-Matching Variant to Mr. Scott, so Mr. Scott does NOT match the tester. Mr. Scott also does NOT match the tester at locations 222222 and 444444.

In example #5, 111111 is NOT shown on the Non-Matching Variant list, so Mr. Treacy DOES match the tester.

I have a terrible time wrapping my head around the double negatives, so it’s critical that I make charts.

On the chart below, I’ve listed the tester’s private variants in an individual column each, so 111111, 222222, etc.

For each match, I’ve copy and pasted their Non-Matching Variants in a column to the right of the tester’s variants, in the lavender region. In this example, I’ve typed the example variants into separate columns for each tester so you can see the difference. Remember, a non-matching variant means they do NOT match the tester’s mutation.

McNiel private variants spreadsheet

On my normal spreadsheet where the non-matching variants don’t have individuals columns, I then search for the first variant, 111111. If the variant does appear in the list, it means that match #1 does NOT have the mutation, so I DON’T put an X in the box for match #1 under 111111.

In the example above, the only match that does NOT have 111111 on their list of Non-Matching Variants is #5, so an X IS placed in that corresponding cell. I’ve highlighted that column in yellow to indicate this is a candidate for a new SNP.

You can see that no one else has the variant, 222222, so it truly is totally private. It’s not highlighted in yellow because it’s not a candidate to be a new SNP.

Everyone shares mutation 333333, so it’s a great candidate to become a new SNP, as is 555555.

Match #6 shares the mutation at 444444, but no one else does.

This is a manual illustration of an automated process that occurs at Family Tree DNA. After Big Y matches are returned, automated software creates private variant lists of potential new haplogroups that are then reviewed internally where SNPs are evaluated, named, and placed on the tree if appropriate.

If you follow this process and discover matches, you probably don’t need to do anything, as the automated review process will likely catch up within a few days to weeks.

Big Y Matches

In the case of the McNiel line, it was exciting to discover several private variants, mutations that were not yet named SNPs, found in several matches that were candidates to be named as SNPs and placed on the Y haplotree.

Sure enough, a few days later, my McNeill cousin had a new haplogroup assignment.

Most people have at least one Private Variant, locations in which they do NOT match another tester. When several people have these same mutations, and they are high-quality reads, the Private Variant qualifies to be added to the haplotree as a SNP, a task performed at FamilyTreeDNA by Michael Sager.

If you ever have the opportunity to hear Michael speak, please do so. You can watch Michael’s presentation at Genetic Genealogy Ireland (GGI) titled “The Tree of Mankind,” on YouTube, here, compliments of Maurice Gleeson who coordinates GGI. Maurice has also written about the Gleeson Y DNA project analysis, here.

As a result of Cousin McNeill’s test, six new SNPs have been added to the Y haplotree, the tree of mankind. You can see our new haplogroup for our branch, BY18332, with an equivalent SNP, BY25938, along with three sibling branches to the left and right on the tree.

McNiel Big Y block tree 4 branch

Big Y testing not only answers genealogical questions, it advances science by building out the tree of mankind too.

The surname of the men who share the same haplogroup, R-BY18332, meaning the named SNP furthest down the tree, are McCollum and Campbell. Not what I expected. I expected to find a McNeil who does match on at least some STR markers. This is exactly why the Big Y is so critical to define the tree structure, then use STR matches to flesh it out.

Taking the Big Y-700 test provided granularity between 6 matches, shown above, who were all initially assigned to the same branch of the tree, BY18350, but were subsequently divided into 4 separate branches. My McNiel cousin is no longer equally as distant from all 6 men. We now know that our McNiel line is genetically closer on the Y chromosome to Campbell and McCollum and further distant from Murphy, Scott, McMichael, and Glass.

Not All SNP Matches are STR Matches

Not all SNP matches are also STR matches. Some relationships are too far back in time. However, in this case, while each person on the BY18350 branches matches at some STR level, only the Campbell individual matches at all STR levels.

Remember that variants (mutations) are accumulating down both respective branches of the tree at the same time, meaning one per roughly every 100 years (if 100 is the average number we want to use) for both testers. A total of 30 variants or mutations difference, an average of 15 on each branch of the tree (McNiel and their match) would suggest a common ancestor about 1500 years ago, so each Big Y match should have a common ancestor 1500 years ago or closer. At least on average, in theory.

The Big Y test match threshold is 30 variants, so if there were any more mismatches with the Campbell male, they would not have been a Big Y match, even though they have the exact same haplogroup.

Having the same haplogroup means that their terminal SNP is identical, the SNP furthest down the tree today, at least until someone matches one of them on their Private Variants (if any remain unnamed) and a new terminal SNP is assigned to one or both of them.

Mutations, and when they happen, are truly a roll of the dice. This is why viewing all of your Big Y Block Tree matches is critical, even if they don’t show on your Big Y match list. One more variant and Campbell would have not been shown as a match, yet he is actually quite close, on the same branch, and matches on all STR panels as well.

SNPs Establish the Backbone Structure

I always view the block tree first to provide a branching tree structure, then incorporate STR matches into the equation. Both can equally as important to genealogy, but haplogroup assignment is the most accurate tool, regardless of whether the two individuals match on the Big Y test, especially if the haplogroups are relatively close.

Let’s work with the Block Tree.

The Block Tree

McNIel Big Y block tree menu

Clicking on the link to the Block Tree in the Big Y results immediately displays the tester’s branch on the tree, below.

click to enlarge

On the left side are SNP generation markers. Keep in mind that approximate SNP generations are marked every 5 generations. The most recent generations are based on the number of private variants that have not yet been assigned as branches on the tree. It’s possible that when they are assigned that they will be placed upstream someplace, meaning that placement will reduce the number of early branches and perhaps increase the number of older branches.

The common haplogroup of all of the branches shown here with the upper red arrow is R-BY3344, about 15 SNP generations ago. If you’re using 100 years per SNP generation, that’s about 1500 years. If you’re using 80 years, then 1200 years ago. Some people use even fewer years for calculations.

If some of the private variants in the closer branches disappear, then the common ancestral branch may shift to closer in time.

This tree will always be approximate because some branches can never be detected. They have disappeared entirely over time when no males exist to reproduce.

Conversely, subclades have been born since a common ancestor clade whose descendants haven’t yet tested. As more people test, more clades will be discovered.

Therefore, most recent common ancestor (MRCA) haplogroup ages can only be estimated, based on who has tested and what we know today. The tree branches also vary depending on whether testers have taken the Big Y-500 or the more sensitive Big Y-700, which detects more variants. The Y haplotree is a combination of both.

Big Y-500 results will not be as granular and potentially do not position test-takers as far down the tree as Big Y-700 results would if they upgraded. You’ll need to factor that into your analysis if you’re drawing genealogical conclusions based on these results, especially close results.

You’ll note that the direct path of descent is shown above with arrows from BY3344 through the first blue box with 5 equivalent SNPS, to the next white box, our branch, with two equivalent SNPs. Our McNeil ancestor, the McCollum tester, and the Campell tester have no unresolved private variants between them, which suggests they are probably closer in time than 10 generations back. You can see that the SNP generations are pushed “up” by the neighbor variants.

Because of the fact that private variants don’t occur on a clock cycle and occur in individual lines at an unsteady rate, we must use averages.

That means that when we look further “up” the tree, clicking generation by generation on the up arrow above BY3344, the SNP generations on the left side “adjust” based on what is beneath, and unseen at that level.

The Block Tree Adjusts

Note, in the example above, BY3344 is at SNP generation 15.

Next, I clicked one generation upstream, to R-S668.

McNiel Big Y block tree S668

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You can see that S668 is about 21 SNP generations upstream, and now BY3344 is listed as 20 generations, not 15. You can see our branch, BY3344, but you can no longer see subclades or our matches below that branch in this view.

You can, however, see two matches that descend through S668, brother branches to BY3344, red arrows at far right.

Clicking on the up arrow one more time shows us haplogroup S673, below, and the child branches. The three child branches on which the tester has matches are shown with red arrows.

McNiel Big Y S673

click to enlarge

You’ll immediately notice that now S668 is shown at 19 SNP generations, not 20, and S673 is shown at 20. This SNP generation difference between views is a function of dealing with aggregated and averaged private variants on combined lines and causes the SNP generations to shift. This is also why I always say “about.”

As you continue to click up the tree, the shifting SNP generations continue, reminding us that we can’t truly see back in time. We can only achieve approximations, but those approximations improve as more people test, and more SNPs are named and placed in their proper places on the phylotree.

I love the Block Tree, although I wish I could see further side-to-side, allowing me to view all of the matches on one expanded tree so I can easily see their relationships to the tester, and each other.

Countries and Origins

In addition to displaying shared averaged autosomal origins of testers on a particular branch, if they have taken the Family Finder test and opted-in to sharing origins (ethnicity) results, you can also view the countries indicated by testers on that branch along with downstream branches of the tree.

McNiel Big Y countries

click to enlarge

For example, the Countries tab for S673 is shown above. I can see matches on this branch with no downstream haplogroup currently assigned, as well as cumulative results from downstream branches.

Still, I need to be able to view this information in a more linear format.

The Block Tree and spreadsheet information beautifully augment the haplotree, so let’s take a look.

The Haplotree

On your Y DNA results page, click on the “Haplotree and SNPs” link.

McNIel Big Y haplotree menu

click to enlarge

The Y haplotree will be displayed in pedigree style, quite familiar to genealogists. The SNP legend will be shown at the top of the display. In some cases, “presumed positive” results occur where coverage is lacking, back mutations or read errors are encountered. Presumed positive is based on positive SNPs further down the tree. In other words, that yellow SNP below must read positive or downstream ones wouldn’t.

McNIel Big Y pedigree descent

click to enlarge

The tester’s branch is shown with the grey bar. To the right of the haplogroup-defining SNP are listed the branch and equivalent SNP names. At far right, we see the total equivalent SNPs along with three dots that display the Country Report. I wish the haplotree also showed my matches, or at least my matching surnames, allowing me to click through. It doesn’t, so I have to return to the Big Y page or STR Matches page, or both.

I’ve starred each branch through which my McNiell cousin descends. Sibling branches are shown in grey. As you’ll recall from the Block Tree, we do have matches on those sibling branches, shown side by side with our branch.

The small numbers to the right of the haplogroup names indicate the number of downstream branches. BY18350 has three, all displayed. But looking upstream a bit, we see that DF97 has 135 downstream branches. We also have matches on several of those branches. To show those branches, simply click on the haplogroup.

The challenge for me, with 119 McNeill matches, is that I want to see a combination of the block tree, my spreadsheet information, and the haplotree. The block tree shows the names, my spreadsheet tells me on which branches to look for those matches. Many aren’t easily visible on the block tree because they are downstream on sibling branches.

Here’s where you can find and view different pieces of information.

Data and Sources STR Matches Page Big Y Matches Page Block Tree Haplogroups & SNPs Page
STR matches Yes No, but would like to see who matches at which STR levels If they have taken Big Y test, but doesn’t mean they match on Big Y matching No
SNP matches *1 Shows if STR match has common haplogroup, but not if tester matches on Big Y No, but would like to see who matches at which STR level Big Y matches and STR matches that aren’t Big Y matches are both shown No, but need this feature – see combined haplotree/ block tree
Other Haplogroup Branch Residents Yes, both estimated and tested No, use block tree or click through to profile card, would like to see haplogroup listed for Big Y matches Yes, both Big Y and STR tested, not estimated. Cannot tell if person is Big Y match or STR match, or both. No individuals, but would like that as part of countries report, see combined haplotree/block tree
Fully Expanded Phylotree No No Would like ability to see all branches with whom any Big Y or STR match resides at one time, even if it requires scrolling Yes, but no match information. Matches report could be added like on Block Tree.
Averaged Ethnicities if Have FF Test No No Yes, by haplogroup branch No
Countries Matches map STR only No, need Big Y matches map Yes Yes
Earliest Known Ancestor Yes No, but can click through to profile card No No
Customer Trees Yes No, need this link No No
Profile Card Yes, click through Yes, click through Yes, click through No match info on this page
Downloadable data By STR panel only, would like complete download with 1 click, also if Big Y or FF match Not available at all No No
Path to common haplogroup No No, but would like to see matches haplogroup and convergent haplogroup displayed No, would like the path to convergent haplogroup displayed as an option No, see combined match-block -haplotree in next section

*1 – the best way to see the haplogroup of a Big Y match is to click on their name to view their profile card since haplogroup is not displayed on the Big Y match page. If you happen to also match on STRs, their haplogroup is shown there as well. You can also search for their name using the block tree search function to view their haplogroup.

Necessity being the mother of invention, I created a combined match/block tree/haplotree.

And I really, REALLY hope Family Tree DNA implements something like this because, trust me, this was NOT fun! However, now that it’s done, it is extremely useful. With fewer matches, it should be a breeze.

Here are the steps to create the combined reference tree.

Combo Match/Block/Haplotree

I used Snagit to grab screenshots of the various portions of the haplotree and typed the surnames of the matches in the location of our common convergent haplogroup, taken from the spreadsheet. I also added the SNP generations in red for that haplogroup, at far left, to get some idea of when that common ancestor occurred.

McNIel Big Y combo tree

click to enlarge

This is, in essence, the end-goal of this exercise. There are a few steps to gather data.

Following the path of two matches (the tester and a specific match) you can find their common haplogroup. If your match is shown on the block tree in the same view with your branch, it’s easy to see your common convergent parent haplogroup. If you can’t see the common haplogroup, it’s takes a few extra steps by clicking up the block tree, as illustrated in an earlier section.

We need the ability to click on a match and have a tree display showing both paths to the common haplogroup.

McNiel Big Y convergent

I simulated this functionality in a spreadsheet with my McNiel cousin, a Riley match, and an Ocain match whose terminal SNP is the convergent SNP (M222) between Riley and McNiel. Of course, I’d also like to be able to click to see everyone on one chart on their appropriate branches.

Combining this information onto the haplotree, in the first image, below, M222, 4 men match my McNeill cousin – 2 who show M222 as their terminal SNP, and 2 downstream of M222 on a divergent branch that isn’t our direct branch. In other words, M222 is the convergence point for all 4 men plus my McNeill cousin.

McNiel Big Y M222 haplotree

click to enlarge

In the graphic below, you can see that M222 has a very large number of equivalent SNPs, which will likely become downstream haplogroups at some point in the future. However, today, these equivalent SNPs push M222 from 25 generations to 59. We’ll discuss how this meshes with known history in a minute.

McNiel Big Y M222 block tree

click to enlarge

Two men, Ocain and Ransom, who have both taken the Big Y, whose terminal SNP is M222, match my McNiel cousin. If their common ancestor was actually 59 generations in the past, it’s very, very unlikely that they would match at all given the 30 mutation threshold.

On my reconstructed Match/Block/Haplotree, I included the estimated SNP generations as well. We are starting with the most distant haplogroups and working our way forward in time with the graphics, below.

Make no mistake, there are thousands more men who descend from M222 that have tested, but all of those men except 4 have more than 30 mutations total, so they are not shown as Big Y matches, and they are not shown individually on the Block Tree because they neither match on the Big Y or STR tests. However, there is a way to view information for non-matching men who test positive for M222.

McNiel Big Y M222 countries

click to enlarge

Looking at the Block Tree for M222, many STR match men took a SNP test only to confirm M222, so they would be shown positive for the M222 SNP on STR results and, therefore, in the detailed view of M222 on the Block tree.

Haplogroup information about men who took the M222 test and whom the tester doesn’t match at all are shown here as well in the country and branch totals for R-M222. Their names aren’t displayed because they don’t match the tester on either type of Y DNA test.

Back to constructing my combined tree, I’ve left S658 in both images, above and below, as an overlap placeholder, as we move further down, or towards current, on the haplotree.

McNiel Big Y combo tree center

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Note that BY18350, above, is also an overlap connecting below.

You’ll recall that as a result of the Big Y test, BY18350 was split and now has three child branches plus one person whose terminal SNP is BY18350. All of the men shown below were on one branch until Big Y results revealed that BY18350 needed to be split, with multiple new haplogroups added to the tree.

McNiel Big Y combo tree current

click to enlarge

Using this combination of tools, it’s straightforward for me to see now that our McNiel line is closest to the Campbell tester from Scotland according to the Big Y test + STRs.

Equal according to the Big Y test, but slightly more distant, according to STR matching, is McCollum. The next closest would be sibling branches. Then in the parent group of the other three, BY18350, we find Glass from Scotland.

In BY18350 and subgroups, we find several Scotland locations and one Northern Ireland, which was likely from Scotland initially, given the surname and Ulster Plantation era.

The next upstream parent haplogroup is BY3344, which looks to be weighted towards ancestors from Scotland, shown on the country card, below.

McNiel Big Y BY3344

click to enlarge

This suggests that the origins of the McNiel line was, perhaps, in Scotland, but it doesn’t tell us whether or not George and presumably, Thomas, immigrated from Ireland or Scotland.

This combined tree, with SNPs, surnames from Big Y matches, along with Country information, allows me to see who is really more closely related and who is further away.

What I didn’t do, and probably should, is to add in all of the STR matches who have taken the Big Y test, shown on their convergent branch – but that’s just beyond the scope of time I’m willing to invest, at least for now, given that hundreds of STR matches have taken the Big Y test, and the work of building the combined tree is all manual today.

For those reading this article without access to the Y phylogenetic tree, there’s a public version of the Y and mitochondrial phylotrees available, here.

What About Those McNiels?

No other known McNiel descendants from either Thomas or George have taken the Big Y test, so I didn’t expect any to match, but I am interested in other men by similar surnames. Does ANY other McNiel have a Big Y match?

As it turns out, there are two, plus one STR match who took a Big Y test, but is not a Big Y match.

However, as you can see on the combined match/block/haplotree, above, the closest other Big Y-matching McNeil male is found at about 19 SNP generations, or roughly 1900 years ago. Even if you remove some of the variants in the lower generations that are based on an average number of individual variants, you’re still about 1200 years in the past. It’s extremely doubtful that any surname would survive in both lines from the year 800 or so.

That McNeil tester’s ancestor was born in 1747 in Tranent, Scotland.

The second Big Y-matching person is an O’Neil, a few branches further up in the tree.

The convergent SNP of the two branches, meaning O’Neil and McNeill are at approximately the 21 generation level. The O’Neil man’s Neill ancestor is found in 1843 in Cookestown, County Tyrone, Ireland.

McNiel Big Y convergent McNeil lines

I created a spreadsheet showing convergent lines:

  • The McNeill man with haplogroup A4697 (ancestor Tranent, Scotland) is clearly closest genetically.
  • O’Neill BY91591, who is brother clades with Neel and Neal, all Irish, is another Big Y match.
  • The McNeill man with haplogroup FT91182 is an STR match, but not a Big Y match.

The convergent haplogroup of all of these men is DF105 at about the 22 SNP generation marker.

STRs

Let’s turn back to STR tests, with results that produce matches closer in time.

Searching my STR download spreadsheet for similar surnames, I discovered several surname matches, mining the Earliest Known Ancestor information, profiles and trees produced data as follows:

Ancestor STR Match Level Location
George Charles Neil 12, 25, match on Big Y A4697 1747-1814 Tranent, Scotland
Hugh McNeil 25 (tested at 67) Born 1800 Country Antrim, Northern Ireland
Duncan McNeill 12 (tested at 111) Married 1789, Argyllshire, Scotland
William McNeill 12, 25 (tested at 37) Blackbraes, Stirlingshire, Scotland
William McNiel 25 (tested at 67) Born 1832 Scotland
Patrick McNiel 25 (tested at 111) Trien East, County Roscommon, Ireland
Daniel McNeill 25 (tested at 67) Born 1764 Londonderry, Northern Ireland
McNeil 12 (tested at 67) 1800 Ireland
McNeill (2 matches) 25 (tested Big Y-  SNP FT91182) 1810, Antrim, Northern Ireland
Neal 25 – (tested Big Y, SNP BY146184) Antrim, Northern Ireland
Neel (2 matches) 67 (tested at 111, and Big Y) 1750 Ireland, Northern Ireland

Our best clue that includes a Big Y and STR match is a descendant of George Charles Neil born in Tranent, Scotland, in 1747.

Perhaps our second-best clue comes in the form of a 111 marker match to a descendant of one Thomas McNeil who appears in records as early as 1753 and died in 1761 In Rombout Precinct, Dutchess County, NY where his son John was born. This line and another match at a lower level both reportedly track back to early New Hampshire in the 1600s.

The MacNeil DNA Project tells us the following:

Participant 106370 descends from Isaiah McNeil b. 14 May 1786 Schaghticoke, Rensselaer Co. NY and d. 28 Aug 1855 Poughkeepsie, Dutchess Co., NY, who married Alida VanSchoonhoven.

Isaiah’s parents were John McNeal, baptized 21 Jun 1761 Rombout, Dutchess Co., NY, d. 15 Feb 1820 Stillwater, Saratoga Co., NY and Helena Van De Bogart.

John’s parents were Thomas McNeal, b.c. 1725, d. 14 Aug 1761 NY and Rachel Haff.

Thomas’s parents were John McNeal Jr., b. around 1700, d. 1762 Wallkill, Orange Co., NY (now Ulster Co. formed 1683) and Martha Borland.

John’s parents were John McNeal Sr. and ? From. It appears that John Sr. and his family were this participant’s first generation of Americans.

Searching this line on Ancestry, I discovered additional information that, if accurate, may be relevant. This lineage, if correct, and it may not be, possibly reaching back to Edinburgh, Scotland. While the information gathered from Ancestry trees is certainly not compelling in and of itself, it provides a place to begin research.

Unfortunately, based on matches shown on the MacNeil DNA Project public page, STR marker mutations for kits 30279, B78471 and 417040 when compared to others don’t aid in clustering or indicating which men might be related to this group more closely than others using line-marker mutations.

Matches Map

Let’s take a look at what the STR Matches Map tells us.

McNiel Big Y matches map menu

This 67 marker Matches Map shows the locations of the earliest known ancestors of STR matches who have entered location information.

McNiel Big Y matches mapMcNiel Big Y matches map legend

My McNeill cousin’s closest matches are scattered with no clear cluster pattern.

Unfortunately, there is no corresponding map for Big Y matches.

SNP Map

The SNP map provided under the Y DNA results allows testers to view the locations where specific haplogroups are found.

McNiel Big Y SNP map

The SNP map marks an area where at least two or more people have claimed their most distant known ancestor to be. The cluster size is the maximum amount of miles between people that is allowed in order for a marker indicating a cluster at a location to appear. So for example, the sample size is at least 2 people who have tested, and listed their most distant known ancestor, the cluster is the radius those two people can be found in. So, if you have 10 red dots, that means in 1000 miles there are 10 clusters of at least two people for that particular SNP. Note that these locations do NOT include people who have tested positive for downstream locations, although it does include people who have taken individual SNP tests.

Working my way from the McNiel haplogroup backward in time on the SNP map, neither BY18332 nor BY18350 have enough people who’ve tested, or they didn’t provide a location.

Moving to the next haplogroup up the tree, two clusters are formed for BY3344, shown below.

McNIel Big Y BY3344 map

S668, below.

McNiel Big Y S668 map

It’s interesting that one cluster includes Glasgow.

S673, below.

McNiel Big Y S673 map

DF85, below:

McNiel Big Y DF85 map

DF105 below:

McNiel BIg Y DF105 map

M222, below:

McNiel Big Y M222 map

For R-M222, I’ve cropped the locations beyond Ireland and Scotland. Clearly, RM222 is the most prevalent in Ireland, followed by Scotland. Wherever M222 originated, it has saturated Ireland and spread widely in Scotland as well.

R-M222

R-M222, the SNP initially thought to indicate Niall of the 9 Hostages, occurred roughly 25-59 SNP generations in the past. If this age is even remotely accurate, averaging by 80 years per generation often utilized for Big Y results, produces an age of 2000 – 4720 years. I find it extremely difficult to believe any semblance of a surname survived that long. Even if you reduce the time in the past to the historical narrative, roughly the year 400, 1600 years, I still have a difficult time believing the McNiel surname is a result of being a descendant of Niall of the 9 Hostages directly, although oral history does have staying power, especially in a clan setting where clan membership confers an advantage.

Surname or not, clearly, our line along with the others whom we match on the Big Y do descend from a prolific common ancestor. It’s very unlikely that the mutation occurred in Niall’s generation, and much more likely that other men carried M222 and shared a common ancestor with Niall at some point in the distant past.

McNiel Conclusion – Is There One?

If I had two McNiel wishes, they would be:

  • Finding records someplace in Virginia that connect George and presumably brothers Thomas and John to their parents.
  • A McNiel male from wherever our McNiel line originated becoming inspired to Y DNA test. Finding a male from the homeland might point the way to records in which I could potentially find baptismal records for George about 1720 and Thomas about 1724, along with possibly John, if he existed.

I remain hopeful for a McNiel from Edinburgh, or perhaps Glasgow.

I feel reasonably confident that our line originated genetically in Scotland. That likely precludes Niall of the 9 Hostages as a direct ancestor, but perhaps not. Certainly, one of his descendants could have crossed the channel to Scotland. Or, perhaps, our common ancestor is further back in time. Based on the maps, it’s clear that M222 saturates Ireland and is found widely in Scotland as well.

A great deal depends on the actual age of M222 and where it originated. Certainly, Niall had ancestors too, and the Ui Neill dynasty reaches further back, genetically, than their recorded history in Ireland. Given the density of M222 and spread, it’s very likely that M222 did, in fact, originate in Ireland or, alternatively, very early in Scotland and proliferated in Ireland.

If the Ui Neill dynasty was represented in the persona of the High King, Niall of the 9 Hostages, 1600 years ago, his M222 ancestors were clearly inhabiting Ireland earlier.

We may not be descended from Niall personally, but we are assuredly related to him, sharing a common ancestor sometime back in the prehistory of Ireland and Scotland. That man would sire most of the Irish men today and clearly, many Scots as well.

Our ancestors, whoever they were, were indeed in Ireland millennia ago. R-M222, our ancestor, was the ancestor of the Ui Neill dynasty and of our own Reverend George McNiel.

Our ancestors may have been at Knowth and New Grange, and yes, perhaps even at Tara.

Tara Niall mound in sun

Someplace in the mists of history, one man made a different choice, perhaps paddling across the channel, never to return, resulting in M222 descendants being found in Scotland. His descendants include our McNeil ancestors, who still slumber someplace, awaiting discovery.

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Genetic Affairs: AutoPedigree Combines AutoTree with WATO to Identify Your Potential Tree Locations

July 2020 Update: Please note that Ancestry issues a cease-and-desist order against Genetic Affairs, and this tool no longer works at Ancestry. The great news is that it still works at the other vendors, and you can ask Ancestry matches to transfer, which is free.

If you’re an adoptee or searching for an unknown parent or ancestor, AutoPedigree is just what you’ve been waiting for.

By now, we’re all familiar with Genetic Affairs who launched in 2018 with their signature autocluster tool. AutoCluster groups your matches into clusters by who your matches match with each other, in addition to you.

browser autocluster

A year later, in December 2019, Genetic Affairs introduced AutoTree, automated tree reconstruction based on your matches trees at Ancestry and Family Finder at Family Tree DNA, even if you don’t have a tree.

Now, Genetic Affairs has introduced AutoPedigree, a combination of the AutoTree reconstruction technology combined with WATO, What Are the Odds, as seen here at DNAPainter. WATO is a statistical probability technique developed by the DNAGeek that allows users to review possible positions in a tree for where they best fit.

Here’s the progressive functionality of how the three Genetic Affairs tools, combined, function:

  • AutoCluster groups people based on if they match you and each other
  • AutoTree finds common ancestors for trees from each cluster
  • Next, AutoTree finds the trees of all matches combined, including from trees of your DNA matches not in clusters
  • AutoPedigree checks to see if a common ancestor tree meets the minimum requirement which is (at least) 3 matches of greater to or equal to 30-40 cM. If yes, an AutoPedigree with hypotheses is created based on the common ancestor of the matching people.
  • Combined AutoPedigrees then reviews all AutoTrees and AutoPedigrees that have common ancestors and combine them into larger trees.

Let’s look at examples, beginning with DNAPainter who first implemented a form of WATO.

DNA Painter

Let’s say you’re trying to figure out how you’re related to a group of people who descend from a specific ancestral couple. This is particularly useful for someone seeking unknown parents or other unknown relationships.

DNA tools are always from the perspective of the tester, the person whose kit is being utilized.

At DNAPainter, you manually create the pedigree chart beginning with a common couple and creating branches to all of their descendants that you match.

This example at DNAPainter shows the matches with their cM amounts in yellow boxes.

xAutoPedigree DNAPainter WATO2

The tester doesn’t know where they fit in this pedigree chart, so they add other known lines and create hypothesis placeholder possibilities in light blue.

In other words, if you’re searching for your mother and you were born in 1970, you know that your mother was likely born between 1925 (if she was 45 when she gave birth to you) and 1955 (if she was 15 when she gave birth to you.) Therefore, in the family you create, you’d search for parents who could have given birth to children during those years and create hypothetical children in those tree locations.

The WATO tool then utilizes the combination of expected cMs at that position to create scores for each hypothesis position based on how closely or distantly you match other members of that extended family.

The Shared cM Project, created and recently updated by Blaine Bettinger is used as the foundation for the expected centimorgan (cM) ranges of each relationship. DNAPainter has automated the possible relationships for any given matching cM amount, here.

In the graphic above, you can see that the best hypothesis is #2 with a score of 1, followed by #4 and #5 with scores of 3 each. Hypothesis 1 has a score of 63.8979 and hypothesis 3 has a score of 383.

You’ll need to scroll to the bottom to determine which of the various hypothesis are the more likely.

Autopedigree DNAPainter calculated probability

Using DNAPainter’s WATO implementation requires you to create the pedigree tree to test the hypothesis. The benefit of this is that you can construct the actual pedigree as known based on genealogical research. The down-side, of course, is that you have to do the research to current in each line to be able to create the pedigree accurately, and that’s a long and sometimes difficult manual process.

Genetic Affairs and WATO

Genetic Affairs takes a different approach to WATO. Genetic Affairs removes the need for hand entry by scanning your matches at Ancestry and Family Tree DNA, automatically creating pedigrees based on your matches’ trees. In addition, Genetic Affairs automatically creates multiple hypotheses. You may need to utilize both approaches, meaning Genetic Affairs and DNAPainter, depending on who has tested, tree completeness at the vendors, and other factors.

The great news is that you can import the Genetic Affairs reconstructed trees into DNAPainter’s WATO tool instead of creating the pedigrees from scratch. Of course, Genetic Affairs can only use the trees someone has entered. You, on the other hand, can create a more complete tree at DNAPainter.

Combining the two tools leverages the unique and best features of both.

Genetic Affairs AutoPedigree Options

Recently, Genetic Affairs released AutoPedigree, their new tool that utilizes the reconstructed AutoTrees+WATO to place the tester in the most likely region or locations in the reconstructed tree.

Let’s take a look at an example. I’m using my own kit to see what kind of results and hypotheses exist for where I fit in the tree reconstructed from my matches and their trees.

If you actually do have a tree, the AutoTree portion will simply be counted as an equal tree to everyone else’s trees, but AutoPedigree will ignore your tree, creating hypotheses as if it doesn’t exist. That’s great for adoptees who may have hypothetical trees in progress, because that tree is disregarded.

First, sign on to your account at Genetic Affairs and select the AutoPedigree option for either Ancestry or Family Tree DNA which reconstructs trees and generates hypotheses automatically. For AutoPedigree construction, you cannot combine the results from Ancestry and FamilyTreeDNA like you can when reconstructing trees alone. You’ll need to do an AutoPedigree run for each vendor. The good news is that while Ancestry has more testers and matches, FamilyTreeDNA has many testers stretching back 20 years or so in the past who passed away before testing became available at Ancestry. Often, their testers reach back a generation or two further. You can easily transfer Ancestry (and other) results to Family Tree DNA for free to obtain more matches – step-by-step instructions here.

At Genetic Affairs, you should also consider including half-relations, especially if you are dealing with an unknown parent situation. Selecting half-relationships generates very large trees, so you might want to do the first run without, then a second run with half relationships selected.

AutoPedigree options

Results

I ran the program and opened the resulting email with the zip file. Saving that file automatically unzips for me, displaying the following 5 files and folders.

Autopedigree cluster

Clicking on the AutoCluster HTML link reveals the now-familiar clusters, shown below.

Autopedigree clusters

I have a total of 26 clusters, only partially shown above. My first peach cluster and my 9th blue cluster are huge.

Autopedigree 26 clusters

That’s great news because it means that I have a lot to work with.

autopedigree folder

Next, you’ll want to click to open your AutoPedigree folder.

For each cluster, you’ll have a corresponding AutoPedigree file if an AutoPedigree can be generated from the trees of the people in that cluster.

My first cluster is simply too large to show successfully in blog format, so I’m selecting a smaller cluster, #21, shown below with the red arrow, with only 6 members. Why so small, you ask? In part, because I want to illustrate the fact that you really don’t need a lot of matches for the AutoPedigree tool to be useful.

Autopedigree multiple clusters

Note also that this entire group of clusters (blue through brown) has members in more than one cluster, indicated by the grey cells that mean someone is a member of at least 2 clusters. That tells me that I need to include the information from those clusters too in my analysis. Fortunately, Genetic Affairs realizes that and provides a combined AutoPedigree tool for that as well, which we will cover later in the article. Just note for now that the blue through brown clusters seem to be related to cluster 21.

Let’s look at cluster 21.

autopedigree cluster 21

In the AutoPedigree folder, you’ll see cluster files when there are trees available to create pedigrees for individual clusters. If you’re lucky, you’ll find 2 files for some clusters.

autopedigree ancestors

At the top of each cluster AutoPedigree file, Genetic Affairs shows you the home couple of the descendant group shown in the matches and their corresponding trees.

Autopedigree WATO chart

Image 1 – click to enlarge

I don’t expect you to be able to read everything in the above pedigree chart, just note the matches and arrows.

You can see three of my cousins who match, labeled with “Ancestry.” You also see branches that generate a viable hypothesis. When generating AutoPedigrees, Genetic Affairs truncates any branches that cannot result in a viable hypothesis for placing the tester in a viable location on the tree, so you may not see all matches.

Autopedigree hyp 1

Image 2 – click to enlarge

On the top branch, you’ll see hyp-1-child1 which is the first hypothesis, with the first child. Their child is hyp-2- child2, and their child is hyp-3-child3. The tester (me, in this case) cannot be the persons shown with red flags, called badges, based on how I match other people and other tree information such as birth and death dates.

Think of a stoplight, red=no, green are your best bets and the rest are yellow, meaning maybe. AutoPedigree makes no decisions, only shows you options, and calculated mathematically how probable each location is to be correct.

Remember, these “children,” meaning hypothesis 1-child 1 may or may not have actually existed. These relationships are hypothetical showing you that IF these people existed, where the tester could appear on the tree.

We know that I don’t fit on the branch above hypothesis 1, because I only match the descendant of Adam Lentz at 44.2 cM which is statistically too low for me to also inhabit that branch.

I’ve included half relationships, so we see hyp-7-child1-half too, which is a half-sibling.

The rankings for hypotheses 1, 2, and 7 all have red badges, meaning not possible, so they have a score of 0. Hypothesis 3 and 8 are possible, with a ranking of 16, respectively.

autopedigree my location

Image 3 – click to enlarge

Looking now at the next segment of the tree, you see that based on how I match my Deatsman and Hartman cousins, I can potentially fit in any portion of the tree with green badges (in the red boxes) or yellow badges.

You can also see where I actually fit in the tree. HOWEVER, that placement is from AutoTree, the tree reconstruction portion, based on the fact that I have a tree (or someone has a tree with me in it). My own tree is ignored for hypothesis generation for the AutoPedigree hypothesis generation portion.

Had my first cousins once removed through my grandfather John Ferverda’s brother, Roscoe, tested AND HAD A TREE, there would have been no question where I fit based on how I match them.

autopedigree cousins

As it turns out they did test, but provided no tree meaning that Genetic Affairs had no tree to work with.

Remember that I mentioned that my first cluster was huge. Many more matches mean that Genetic Affairs has more to work with. From that cluster, here’s an example of a hypothesis being accurate.

autopedigree correct

Image 4 – click to enlarge

You can see the hypothetical line beneath my own line, with hypothesis 104, 105, 106, 107, 108. The AutoTree portion of my tree is shown above, with my father and grandparents and my name in the green block. The AutoPedigree portion ignores my own tree, therefore generating the hypothesis that’s where I could fit with a rank of 2. And yes, that’s exactly where I fit in the tree.

In this case, there were some hypotheses ranked at 1, but they were incorrect, so be sure to evaluate all good (green) options, then yellow, in that order.

Genetic Affairs cannot work with 23andMe results for AutoPedigree because 23andMe doesn’t provide or support trees on their site. AutoClusters are integrated at MyHeritage, but not the AutoTree or AutoPedigree functions, and they cannot be run separately.

That leaves Family Tree DNA and Ancestry.

Combined AutoPedigree

After evaluating each of the AutoPedigrees generated for each cluster for which an AutoPedigree can be generated, click on the various cluster combined autopedigrees.

autopedigree combined

You can see that for cluster 1, I have 7 separate AutoPedigrees based on common ancestors that were different. I have 3 AutoPedigrees also for cluster 9, and 2 AutoPedigrees for 15, 21, and 24.

I have no AutoPedigrees for clusters 2, 3, 5, 6, 7, 8, 14, 17, 18, and 22.

Moving to the combined clusters, the numbers of which are NOT correlated to the clusters themselves, Genetic Affairs has searched trees and combined ancestors in various clusters together when common ancestors were found.

Autopedigree multiple clusters

Remember that I asked you to note that the above blue through brown clusters seem to have commonality between the clusters based on grey cell matches who are found in multiple groups? In fact, these people do share common ancestors, with a large combined AutoPedigree being generated from those multiple clusters.

I know you can’t read the tree in the image that follows. I’m only including it so you’ll see the scale of that portion of my tree that can be reconstructed from my matches with hypotheses of where I fit.

autopedigree huge

Image 5 – click to enlarge

These larger combined pedigrees are very useful to tie the clusters together and understand how you match numerous people who descend from the same larger ancestral group, further back in time.

Integration with DNAPainter

autopedigree wato file

Each AutoPedigree file and combined cluster AutoPedigree file in the AutoPedigree folder is provided in WATO format, allowing you to import them into DNAPainter’s WATO tool.

autopedigree dnapainter import

You can manually flesh out the trees based on actual genealogy in WATO at DNAPainter, manually add matches from GEDmatch, 23andMe or MyHeritage or matches from vendors where your matches trees may not exist but you know how your match connects to you.

Your AutoTree Ancestors

But wait, there’s more.

autopedigree ancestors folder

If you click on the Ancestors folder, you’ll see 5 options for tree generations 3-7.

autopedigree ancestor generations

My three-generation auto-generated reconstructed tree looks like this:

autopedigree my tree

Selecting the 5th generation level displays Jacob Lentz and Frederica Ruhle, the couple shown in the AutoCluster 21 and AutoPedigree examples earlier. The color-coding indicates the source of the ancestors in that position.

Autopedigree expanded tree

click to enlarge

You will also note that Genetic Affairs indicates how many matches I have that share this common ancestor along with which clusters to view for matches relevant to specific ancestors. How cool is this?!!

Remember that you can also import the genetic match information for each AutoTree cluster found at Family Tree DNA into DNAPainter to paint those matches on your chromosomes using DNAPainter’s Cluster Auto Painter.

If you run AutoCluster for matches at 23andMe, MyHeritage, or FamilyTreeDNA, all vendors who provide segment information, you can also import that cluster segment information into DNAPainter for chromosome painting.

However, from that list of vendors, you can only generate AutoTrees and AutoPedigrees at Family Tree DNA. Given this, it’s in your best interest for your matches to test at or upload their DNA (plus tree) to Family Tree DNA who supports trees AND provides segment information, both, and where you can run AutoTree and AutoPedigree.

Have you painted your clusters or generated AutoTrees? If you’re an adoptee or looking for an unknown parent or grandparent, the new AutoPedigree function is exactly what you need.

Documentation

Genetic Affairs provides complete instructions for AutoPedigree in this newsletter, along with a user manual here, and the Facebook Genetic Affairs User Group can be found here.

I wrote the introductory article, AutoClustering by Genetic Affairs, here, and Genetic Affairs Reconstructs Trees from Genetic Clusters – Even Without Your Tree or Common Ancestors, here. You can read about DNAPainter, here.

Transfer your DNA file, for free, from Ancestry to Family Tree DNA or MyHeritage, by following the easy instructions, here.

Have fun! Your ancestors are waiting.

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Disclosure

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Products and Services

Genealogy Research

 

MyHeritage: Brand New Theories of Family Relativity

MyHeritage has run their Theories of Family Relativity (abbreviated sometimes as TOFR) software again, refreshing their database, which means more Theories of Family Relativity for DNA testers.

According to the MyHeritage blog:

The number of DNA Matches that include a theory increased by 42.5% from 9,964,321 to 14,201,731.

Sometimes we arrive at a theory through multiple paths, indicating a strong theory and providing additional supporting evidence. After the previous update, there were a total of 115,106,944 paths. This update increased the number of paths by 40.5% to 161,762,761.

The number of MyHeritage users who now have at least one Theory of Family Relativity™ for their DNA Matches has increased by 33.6%.

I’m SOOO glad I added all of those branches to my tree, including all children and grandchildren of my ancestors. Every piece of information is utilized in developing Theories.

I sure hope I have new Theories. Let’s see.

My New Theories

Yay, under DNA Matches, I have the purple banner that indicates there are new Theories waiting for me.

Theories new.png

I can just click on View Theories to see all of the TOFR, including new ones.

Theories 65.png

You can see that clicking on the “View theories” button filters my matches to only those matches who have Theories. I have 65 matches, many of whom will have multiple Theories for me to evaluate. That’s an increase from 52 Theories previously, or a 20% increase.

New Theories result from people who have tested or transferred since TOFR was last run in July 2019. Some will be people who can now connect because someone’s tree or research documents now provide enough information to suggest a common ancestor – which of course is the foundation of Theories for DNA matches.

You can sort by new matches, but there isn’t a way to see only your new Theories of Family Relativity. That’s OK, because I make notes on each person with whom I have a Theory, plus I keep a separate spreadsheet.

Theories notes.png

Matches with notes show up with a purple note box. “No notes” have no color, so it’s easy to click through my TOFR matches pages, looking for TOFR matches with no color. Those are new TOFR matches.

Are the New Theories Accurate?

Theories with DNA matches are formed based on a combination of your tree, your matches tree, other people’s trees, community resource trees like FamilySearch, plus various documents like census records that tie people together.

The reason multiple Theories exist for the same match is because there are different possibilities in terms of how you and your match might be related or how different trees might tie you together. In some cases, Theories will be for different lines that you share with the same person.

Each Theory has a confidence calculation that weighs the reliability of each theory connecting segment based on internal parameters. As you can see below, this connection is given a 50% probability weight of being accurate. You can click on that percentage to review the match and comparative data.

Theories weight.png

click to enlarge

Path 1 of my first new Theory is accurate, even though birth and death dates of Ann McKee’s husband are different at FamilySearch.

Theoreis multiple trees.png

click to enlarge

Looking further down this tree, you can see that my match had only extended their tree through Roxie, but a FamilySearch tree spanned the generations between Roxie and our common couple, Charles Speak and Ann McKee.

My tree didn’t extend down far enough to include Roxie.

Of the other 4 paths/Theories, 3 simply connect at different levels in the same basic trees, meaning that I connect at Margaret Claxton instead of Ann McKee.

The 5th path, however, is ambiguous and I can’t tell if it’s accurate or not. It doesn’t matter though, because I have 4 different solid paths connecting me and my new match.

Theories can connect people with almost no tree. One man had a total of 7 people in his tree, yet through multiple connections, we were connected accurately as 5th cousins.

One accurate Theory combined a total of 6 trees to piece together the Theory.

Working the Theories

I stepped through each match, making notes about each Theory, confirming the genealogy, checking for additional surnames that might indicate a second (or third or fourth) line, as well as SmartMatches.

SmartMatches only occur if the same people are found in both trees. I had no SmartMatches this time, because each of these Theories was more complex and required multiple tree hops to make the connection.

One match was a duplicate upload. After eliminating that from the totals, I have the following results for my newly generated Theories of Family Relativity.

Scorecard

Match Total Theories/Paths Accuracy Comments
1 5 4 yes, 1 ambiguous
2 3 Not exactly, but close Close enough that I could easily discern the common ancestor
3 2 Yes
4 5 Yes
5 1 Not exactly, but close Within 1 generation
6 1 No Acadian, needs additional research
7 5 Yes, but 2 with issues 2 were accurate, 2 with ancestor’s first wife erroneously as mother, and one with private mother
8 2 Not exactly, but close Within 1 generation, also, 2 separate lines
9 2 Yes
10 4 Not exactly, but close Within 1 generation
11 5 Yes One wife shown as unknown
12 3 Not exactly, but close Within 1 generation, also 4 separate common lines in total
Total 38 23 yes, 1 ambiguous, 13 close, 1 no

All of the close matches were extremely easy to figure out, except one in a heavily endogamous population with many “same name” people. That one needs additional research.

I’m not at all unhappy with the Theories that weren’t spot on because Theories are meant to be research hints, and they got me to the end goal of identifying our common ancestor.

I wrote about how to use Theories, in detail, here.

Observations and Commentary

Theories of Family Relativity has been run by MyHeritage for the third time now. It doesn’t run all the time, so new testers and uploaders will need to wait until the next run to see their Theories.

You can expect some Theories to come and go, especially if someone has deleted a tree or changed a piece of data that a Theory utilized.

I did not go back and recheck my earlier Theories because I had already ascertained the common ancestor.

I have a total of 65 matches with whom I have TOFR, one of which is a duplicate.

I have a total of 99 paths, or Theories, for those 64 matches.

Of my 64 non-duplicate matches, only 5 don’t have at least one correct Theory. Of those 5, all incorrect Theories are a result of an incorrect tree or name confusion that I was able to easily resolve. Only one needs more research.

Reviewing the match for additional surnames often reveals multiple lines of descent beyond the Theories presented.

Previously, I only had 11 matches with multiple Theories, but of my 12 new matches, only 2 don’t have multiple paths. Multiple Theories are a function of more matches, more trees, and more resources. I’m grateful for all the hints I can get.

Remember, Theories are just that – theories that point you in a research direction. They require confirmation. Good thing we’re genealogists!

Next, DNAPainter

Of course, the good news is that I could paint my new matches at DNAPainter, having assigned them to our common ancestor, thanks to Theories. DNAPainter is a great sanity check. If you have the same reasonably sized segment attributed to multiple ancestors, something is wrong, someplace.

That something could be:

  • That the segment is identical by chance in some matches
  • Someone’s genealogy is inaccurate
  • Imputation added invalid data
  • You’re related in more ways, on more lines, that you know
  • There’s an unknown parentage event in a line someplace
  • That your ancestors were related

What About You?

Do you have new Theories of Family Relativity waiting for you?

Sign on and take a look.

If you haven’t tested at or transferred your DNA to MyHeritage, you can order a test, here. Tests are currently on sale for $39.

MyHeritage offers free transfers from the DNA testing companies whose step-by-step upload instruction articles are listed below.

Instructions for uploading TO MyHeritage are found here:

If you test at MyHeritage, all DNA features, functions, and tools are free.

If you transfer your DNA file to My Heritage, DNA matching is free, but Theories of Family Relativity requires either a site data subscription to access genealogical records, which you can try for free, here, or a one time $29 unlock fee for the advanced DNA tools which include:

  • Theories of Relativity
  • Chromosome browser
  • Triangulation
  • Ethnicity estimates

Have fun!

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Disclosure

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on, and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Products and Services

Genealogy Research

Free MyHeritage Video – Top Tips for Triangulating your DNA Matches With Roberta Estes

Yesterday’s Facebook LIVE presentation for MyHeritage was lots of fun for everyone, and now it’s available for anyone who might have missed it.

I must say, I was stunned that so many people tuned in. We had just under 5000 watching live, with just under 500 comments. There were literally people from all over the world – with perhaps the exception of the locations where it was the dead of night. A day later, there are already more than 9000 views. I hope everyone is enjoying the session.

It felt good to be connected, even if it was electronically. It was still “live.”

I saw people I knew saying “hey,” DNA matches, known cousins, longtime friends, and at least one person with a fairly rare surname from a location that I suspect shares one of my ancestors.

How cool is that?!

For people who are curious about how this works, I was too, so here’s a short explanation.

The Back Story

One day last week, MyHeritage invited me to create this seminar. I thought it would be nice – given that our lives are all disrupted right now.

They suggested half an hour to an hour, including Q&A time, but being just a tad over-zealous, mine went a little long. The entire session, plus Q&A was an hour and a quarter. It’s impossible to do triangulation justice in a short time because the presenter must first explain how and why triangulation works, and why it’s important. You can’t just dive into the middle of that pool.

Also, just to be very clear, I created this video as a volunteer – I wasn’t paid, and I’m not compensated for this or any other article either. I don’t write articles for money or in exchange for anything. If I do receive something, like a book to review that I did not purchase, I say so. My opinions are my own and not for sale.

Working as a member of a worldwide team is interesting, in part because of the time factor. Israel is 7 hours different from my time in the US, so our practice session on Sunday was quite late for their team members, Esther who you met online and Talya, working behind the scenes.

The underlying platform is a product called BeLive which records the session, provides the chat capability and interfaces with Facebook. This means that the computers, cameras and audio (headsets) of all of the people involved must all be compatible with BeLive, given that Esther and Talya are moderating and handling things like which screen is showing and moderating the chat questions. The speaker really can’t do any more than focus on their topic.

I had planned to use my laptop to present against the backdrop of my fireplace in the living room. If you’re going to have a few thousand people “over,” you might as well hostess in the nicest part of your home, right?

BeLive was challenging on my end, to put it mildly. My husband and I both spent several hours, as did Talya and Esther, trying to make things work. The camera and audio on my laptop worked just fine using other platforms, like Skype and Google Hangouts – but absolutely refused to work with BeLive. Even BeLive technical support was baffled. Nothing worked – although my husband, not to be bested by a computer, installed the desktop version of BeLive (which wasn’t supposed to be necessary), then uninstalled the plugins and reinstalled them, toggled the camera, and it magically began to work. But by that time, I had already changed courses.

Compounding the challenge, my laptop, in the midst of those efforts, just died – as in spontaneously went entirely black. No, the battery wasn’t dead, and no, I didn’t have confidence after that. I was afraid that “sudden death” would happen in the middle of the presentation. I always have to be vigilant, because Murphy lives with me and is ever-present, always lurking about.

I made the decision to shift to my desktop. It’s a newer system, but so new that it’s not entirely configured yet, I hadn’t yet used it for webinars, and I’m not completely familiar with how things work in that new environment either.

Thankfully, BeLive worked well on the desktop system and we were able to complete our practice run. It was past time for Talya and Esther to hit the hay, but I needed to clean my office, at least the part behind and beside me, where viewers could see.

So, if you’re wondering if my desk is always entirely clear, the answer would be a resounding “no.” I wasn’t about to have a messy office with company coming over😊

Actually, one of the things I liked when I watched the other MyHeritage Facebook LIVE sessions with Daniel Horowitz and Ran Snir was the homey nature. You know the presenters are recording from someplace in their house and I felt grateful to them for making that extra effort.

DNA Kits Aren’t Quarantined

You might not be able to visit grandma or your relatives, but you can still order DNA tests and have them delivered through the mail. Mother’s Day is May 10th. Order those DNA tests, here. Your gift to them and their DNA gift to you will continue solving family mysteries forever.

The Video

Now that you’ve learned more about the video production aspect than you ever wanted to know, you can watch the presentation online by clicking on the video, below. This part is super easy!

Note that it has been reported that this embedded link is not viewable in Firefox, so please use Chrome. If you do not see the video displayed below and can’t click to view, just click here.

Enjoy!!!

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Disclosure

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Products and Services

Genealogy Research

Top Tips for Triangulating Your DNA Matches with Roberta Estes – FREE – MyHeritage Facebook LIVE, April 27th

MyHeritage Facebook LIVE.png

Yes, I know this is last minute, but consider this seminar a surprise gift, jointly, from me and MyHeritage😊

Top Tips for Triangulating Your DNA Matches is free for everyone!

I’ll readily admit that presenting via Facebook LIVE is new to me, but we will make this work, I promise.

Tomorrow, Monday, April 27th, 2020 at 2 PM EST, on the MyHeritage Facebook page, I’ll be giving a free presentation, with Q&A, about triangulating your DNA matches at MyHeritage.

About Triangulation

Triangulation is both a tool and a process.

Have you wondered any of the following:

  • What is triangulation?
  • Why do I need to triangulate?
  • Why does triangulation work?
  • How do I triangulate?
  • How do I find matches to triangulate?
  • How does triangulation confirm ancestors?
  • How can I use triangulation in my genealogy?
  • Am I using all the tools to find triangulated matches?

If you’d like to learn more about any of those questions, or you’d like to join in for the fun and camaraderie, I’ll see you tomorrow at 2 PM EDT on the MyHeritage Facebook page.

Test or Transfer

If you haven’t yet tested your DNA with MyHeritage, or transferred your DNA to MyHeritage from elsewhere, now is the perfect time! You’ll find step-by-step transfer instructions, here.

Click here to purchase a DNA test, or here to upload a file from another vendor. You’ll have matches to triangulate before you know it!

See You Monday!!

Click here for the MyHeritage Facebook page where the Facebook LIVE event will take place Monday, April 27th, at 2 PM EST!

_____________________________________________________________

Disclosure

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Products and Services

Genealogy Research

Concepts: Chromosome Browser – What Is It, How Do I Use It, and Why Do I Care?

The goal of genetic genealogy is to utilize DNA matches to verify known ancestors and identify unknown ancestors.

A chromosome browser is a tool that allows testers to visualize and compare their DNA on each chromosome with that of their genetic matches. How to utilize and interpret that information becomes a little more tricky.

I’ve had requests for one article with all the information in one place about chromosome browsers:

  • What they are
  • How and when to use them
  • Why you’d want to

I’ve included a feature comparison chart and educational resource list at the end.

I would suggest just reading through this article the first time, then following along with your own DNA results after you understand the basic landscape. Using your own results is the best way to learn anything.

What Does a Chromosome Browser Look Like?

Here’s an example of a match to my DNA at FamilyTreeDNA viewed on their chromosome browser.

browser example.png

On my first 16 chromosomes, shown above, my 1C1R (first cousin once removed,) Cheryl, matches me where the chromosomes are painted blue. My chromosome is represented by the grey background, and her matching portion by the blue overlay.

Cheryl matches me on some portion of all chromosomes except 2, 6, and 13, where we don’t match at all.

You can select any one person, like Cheryl, from your match list to view on a chromosome browser to see where they match you on your chromosomes, or you can choose multiple matches, as shown below.

browser multiple example.png

I selected my 7 closest matches that are not my immediate family, meaning not my parents or children. I’m the background grey chromosome, and each person’s match is painted on top of “my chromosome” in the location where they match me. You see 7 images of my grey chromosome 1, for example, because each of the 7 people being compared to me are shown stacked below one another.

Everyplace that Cheryl matches me is shown on the top image of each chromosome, and our matching segment is shown in blue. The same for the second red copy of the chromosome, representing Don’s match to me. Each person I’ve selected to match against is shown by their own respective color.

You’ll note that in some cases, two people match me in the same location. Those are the essential hints we are looking for. We’ll be discussing how to unravel, interpret, and use matches in the rest of this article.

browser MyHeritage example.png

The chromosome browser at MyHeritage looks quite similar. However, I have a different “top 7” matches because each vendor has people who test on their platform who don’t test or transfer elsewhere.

Each vendor that supports chromosome browsers (FamilyTreeDNA, MyHeritage, 23andMe, and GedMatch) provides their own implementation, of course, but the fundamentals of chromosome browsers, how they work and what they are telling us is universal.

Why Do I Need a Chromosome Browser?

“But,” you might say, “I don’t need to compare my DNA with my matches because the vendors already tell me that I match someone, which confirms that we are related and share a common ancestor.”

Well, not exactly. It’s not quite that straightforward.

Let’s take a look at:

  • How and why people match
  • What matches do and don’t tell you
  • Both with and without a chromosome browser

In part, whether you utilize a chromosome browser or not depends on which of the following you seek:

  • A broad-brush general answer; yes or no, I match someone, but either I don’t know how are related, or have to assume why. There’s that assume word again.
  • To actually confirm and prove your ancestry, getting every ounce of value out of your DNA test.

Not everyone’s goals are the same. Fortunately, we have an entire toolbox with a wide range of tools. Different tools are better suited for different tasks.

People seeking unknown parents should read the article, Identifying Unknown Parents and Individuals Using DNA Matching because the methodology for identifying unknown parents is somewhat different than working with genealogy. This article focuses on genealogy, although the foundation genetic principles are the same.

If you’re just opening your DNA results for the first time, the article, First Steps When Your DNA Results are Ready – Sticking Your Toe in the Genealogy Water would be a great place to start.

Before we discuss chromosome browsers further, we need to talk about DNA inheritance.

Your Parents

Every person has 2 copies of each of their 22 chromosomes – one copy contributed by their mother and one copy contributed by their father. A child receives exactly half of the autosomal DNA of each parent. The DNA of each parent combines somewhat randomly so that you receive one chromosome’s worth of DNA from each of your parents, which is half of each parent’s total.

On each chromosome, you receive some portion of the DNA that each parent received from their ancestors, but not exactly half of the DNA from each individual ancestor. In other words, it’s not sliced precisely in half, but served up in chunks called segments.

Sometimes you receive an entire segment of an ancestor’s DNA, sometimes none, and sometimes a portion that isn’t equal to half of your parent’s segment.

browser inheritance.png

This means that you don’t receive exactly half of the DNA of each of your grandparents, which would be 25% each. You might receive more like 22% from one maternal grandparent and 28% from the other maternal grandparent for a total of 50% of the DNA you inherit from your parents. The other 50% of your DNA comes from the other parent, of course. I wrote about that here.

There’s one tiny confounding detail. The DNA of your Mom and Dad is scrambled in you, meaning that the lab can’t discern scientifically which side is which and can’t tell which pieces of DNA came from Mom and which from Dad. Think of a genetic blender.

Our job, using genetic genealogy, is to figure out which side of our family people who match us descend from – which leads us to our common ancestor(s).

Parallel Roads

For the purposes of this discussion, you’ll need to understand that the two copies you receive of each chromosome, one from each parent, have the exact same “addresses.” Think of these as parallel streets or roads with identical addresses on each road.

browser street.png

In the example above, you can see Dad’s blue chromosome and Mom’s red chromosome as compared to me. Of course, children and parents match on the full length of each chromosome.

I’ve divided this chromosome into 6 blocks, for purposes of illustration, plus the centromere where we generally find no addresses used for genetic genealogy.

In the 500 block, we see that the address of 510 Main (red bar) could occur on either Dad’s chromosome, or Mom’s. With only an address and nothing more, you have no way to know whether your match with someone at 510 Main is on Mom’s or Dad’s side, because both streets have exactly the same addresses.

Therefore, if two people match you, at the same address on that chromosome, like 510 Main Street, they could be:

  • Both maternal matches, meaning both descended from your mother’s ancestors, and those two people will also match each other
  • Both paternal matches, meaning both descended from your father’s ancestors, and those two people will also match each other
  • One maternal and one paternal match, and those two people will not match each other

Well then, how do we know which side of the family a match descends from, and how do we know if we share a common ancestor?

Good question!

Identical by Descent

If you and another person match on a reasonably sized DNA segment, generally about 7 cM or above, your match is probably “identical by descent,” meaning not “identical by chance.” In this case, then yes, a match does confirm that you share a common ancestor.

Identical by descent (IBD) means you inherited the piece of DNA from a common ancestor, inherited through the relevant parent.

Identical by chance (IBC) means that your mom’s and dad’s DNA just happens to have been inherited by you randomly in a way that creates a sequence of DNA that matches that other person. I wrote about both IBD and IBC here.

MMB stats by cM 2

This chart, courtesy of statistician Philip Gammon, from the article Introducing the Match-Maker-Breaker Tool for Parental Phasing shows the percentage of time we expect matches of specific segment sizes to be valid, or identical by descent.

Identical by Chance

How does this work?

How is a match NOT identical by descent, meaning that it is identical by chance and therefore not a “real” or valid match, a situation also known as a false positive?

browser inheritance grid.png

The answer involves how DNA is inherited.

You receive a chromosome with a piece of DNA at every address from both parents. Of course, this means you have two pieces of DNA at each address. Therefore people will match you on either piece of DNA. People from your Dad’s side will match you on the pieces you inherited from him, and people from your Mom’s side will match you on the pieces you inherited from her.

However, both of those matches have the same address on their parallel streets as shown in the illustration, above. Your matches from your mom’s side will have all As, and those from your dad’s side will have all Ts.

The problem is that you have no way to know which pieces you inherited from Mom and from Dad – at least not without additional information.

You can see that for 10 contiguous locations (addresses), which create an example “segment” of your DNA, you inherited all As from your Mom and all Ts from your Dad. In order to match you, someone would either need to have an A or a T in one of their two inherited locations, because you have an A and a T, both. If the other person has a C or a G, there’s no match.

Your match inherited a specific sequence from their mother and father, just like you did. As you can see, even though they do match you because they have either an A or a T in all 10 locations – the As and Ts did not all descend from either their mother or father. Their random inheritance of Ts and As just happens to match you.

If your match’s parents have tested, you won’t match either of their parents nor will they match either of your parents, which tells you immediately that this match is by chance (IBC) and not by descent (IBD), meaning this segment did not come from a common ancestor. It’s identical by chance and, therefore, a false positive.

If We Match Someone Else In Common, Doesn’t That Prove Identical by Descent?

Nope, but I sure wish it did!

The vendors show you who else you and your match both match in common, which provides a SUGGESTION as to your common ancestor – assuming you know which common ancestor any of these people share with you.

browser icw.png

However, shared matches are absolutely NOT a guarantee that you, your match, and your common matches all share the same ancestor, unless you’re close family. Your shared match could match you or your match through different ancestors – or could be identical by chance.

How can we be more confident of what matching is actually telling us?

How can we sort this out?

Uncertainties and Remedies

Here’s are 9 things you DON’T know, based on matching alone, along with tips and techniques to learn more.

  1. If your match to Person A is below about 20cM, you’ll need to verify that it’s a legitimate IBD match (not IBC). You can achieve this by determining if Person A also matches one of your parents and if you match one of Person A’s parents, if parents have tested.

Not enough parents have tested? An alternative method is by determining if you and Person A both match known descendants of the candidate ancestors ON THE SAME SEGMENT. This is where the chromosome browser enters the picture.

In other words, at least three people who are confirmed to descend from your presumptive common ancestor, preferably through at least two different children, must match on a significant portion of the same segment.

Why is that? Because every segment has its own unique genealogical history. Each segment can and often does lead to different ancestors as you move further back in time.

In this example, I’m viewing Buster, David, and E., three cousins descended from the same ancestral couple, compared to me on my chromosome browser. I’m the background grey, and they show in color. You can see that all three of them match me on at least some significant portion of the same segment of chromosome 15.

browser 3 cousins.png

If those people also match each other, that’s called triangulation. Triangulation confirms descent from a common ancestral source.

In this case, I already know that these people are related on my paternal side. The fact that they all match my father’s DNA and are therefore all automatically assigned to my paternal matching tab at Family Tree DNA confirms my paper-trail genealogy.

I wrote detailed steps for triangulation at Family Tree DNA, here. In a nutshell, matching on the same segment to people who are bucketed to the same parent is an automated method of triangulation.

Of course, not everyone has the luxury of having their parents tested, so testing other family members, finding common segments, and assigning people to their proper location in your tree facilitates confirmation of your genealogy (and automating triangulation.)

The ONLY way you can determine if people match you on the same segment, and match each other, is having segment information available to you and utilizing a chromosome browser.

browser MyHeritage triangulation.png

In the example above, the MyHeritage triangulation tool brackets matches that match you (the background grey) and who are all triangulated, meaning they all also match each other. In this case, the portion where all three people match me AND each other is bracketed. I wrote about triangulation at MyHeritage here.

  1. If you match several people who descend from the same ancestor, John Doe, for example, on paper, you CANNOT presume that your match to all of those people is due to a segment of DNA descended from John Doe or his wife. You may not match any of those people BECAUSE OF or through segments inherited from John Doe or his wife. You need segment information and a chromosome browser to view the location of those matches.

Assuming these are legitimate IBD matches, you may share another common line, known or unknown, with some or all of those matches.

It’s easy to assume that because you match and share matches in common with other people who believe they are descended from that same ancestor:

  • That you’re all matching because of that ancestor.
  • Even on the same segments.

Neither of those presumptions can be made without additional information.

Trust me, you’ll get yourself in a heap o’ trouble if you assume. Been there, done that. T-shirt was ugly.

Let’s look at how this works.

browser venn.png

Here’s a Venn diagram showing me, in the middle, surrounded by three of my matches:

  • Match 1 – Periwinkle, descends from Lazarus Estes and Elizabeth Vannoy
  • Match 2 – Teal, descends from Joseph Bolton and Margaret Claxton
  • Match 3 – Mustard, descends from John Y. Estes and Rutha Dodson

Utilizing a chromosome browser, autocluster software, and other tools, we can determine if those matches also match each other on a common segment, which means they triangulate and confirm common ancestral descent.

Of course, those people could match each other due to a different ancestor, not necessarily the one I share with them nor the ancestors I think we match through.

If they/we do all match because they descend from a common ancestor, they can still match each other on different segments that don’t match me.

I’m in the center. All three people match me, and they also match each other, shown in the overlap intersections.

Note that the intersection between the periwinkle (Match 1) and teal (Match 2) people, who match each other, is due to the wives of the children of two of my ancestors. In other words, their match to each other has absolutely nothing to do with their match to me. This was an “aha’ moment for me when I first realized this was a possibility and happens far more than I ever suspected.

The intersection of the periwinkle (Match 1) and mustard (Match 3) matches is due to the Dodson line, but on a different segment than they both share with me. If they had matched each other and me on the same segment, we would be all triangulated, but we aren’t.

The source of the teal (Match 2) to mustard (Match 3) is unknown, but then again, Match 3’s tree is relatively incomplete.

Let’s take a look at autocluster software which assists greatly with automating the process of determining who matches each other, in addition to who matches you.

  1. Clustering technology, meaning the Leeds method as automated by Genetic Affairs and DNAGedcom help, but don’t, by themselves, resolve the quandary of HOW people match you and each other.

People in a colored cluster all match you and each other – but not necessarily on the same segment, AND, they can match each other because they are related through different ancestors not related to your ancestor. The benefit of autocluster software is that this process is automated. However, not all of your matches will qualify to be placed in clusters.

browser autocluster.png

My mustard cluster above includes the three people shown in the chromosome browser examples – and 12 more matches that can be now be researched because we know that they are all part of a group of people who all match me, and several of whom match each other too.

My matches may not match each other for a variety of reasons, including:

  • They are too far removed in time/generations and didn’t inherit any common ancestral DNA.
  • This cluster is comprised of some people matching me on different (perhaps intermarried) lines.
  • Some may be IBC matches.

Darker grey boxes indicate that those people should be in both clusters, meaning the red and mustard clusters, because they match people in two clusters. That’s another hint. Because of the grid nature of clusters, one person cannot be associated with more than 2 clusters, maximum. Therefore, people like first cousins who are closely related to the tester and could potentially be in many clusters are not as useful in clusters as they are when utilizing other tools.

  1. Clusters and chromosome browsers are much less complex than pedigree charts, especially when dealing with many people. I charted out the relationships of the three example matches from the Venn diagram. You can see that this gets messy quickly, and it’s much more challenging to visualize and understand than either the chromosome browser or autoclusters.

Having said that, the ultimate GOAL is to identify how each person is related to you and place them in their proper place in your tree. This, cumulatively with your matches, is what identifies and confirms ancestors – the overarching purpose of genealogy and genetic genealogy.

Let’s take a look at this particular colorized pedigree chart.

Browser pedigree.png

click to enlarge

The pedigree chart above shows the genetic relationship between me and the three matches shown in the Venn diagram.

Four descendants of 2 ancestral couples are shown, above; Joseph Bolton and Margaret Claxton, and John Y. Estes and Rutha Dodson. DNA tells me that all 3 people match me and also match each other.

The color of the square (above) is the color of DNA that represents the DNA segment that I received and match with these particular testers. This chart is NOT illustrating how much DNA is passed in each generation – we already know that every child inherits half of the DNA of each parent. This chart shows match/inheritance coloring for ONE MATCHING SEGMENT with each match, ONLY.

Let’s look at Joseph Bolton (blue) and Margaret Claxton (pink). I descend through their daughter, Ollie Bolton, who married William George Estes, my grandfather. The DNA segment that I share with blue Match 2 (bottom left) is a segment that I inherited from Joseph Bolton (blue). I also carry inherited DNA from Margaret Claxton too, but that’s not the segment that I share with Match 2, which is why the path from Joseph Bolton to me, in this case, is blue – and why Match 2 is blue. (Just so you are aware, I know this segment descends from Joseph Bolton, because I also match descendants of Joseph’s father on this segment – but that generation/mtach is not shown on this pedigree chart.)

If I were comparing to someone else who I match through Margaret Claxton, I would color the DNA from Margaret Claxton to me pink in that illustration. You don’t have to DO this with your pedigree chart, so don’t worry. I created this example to help you understand.

The colored dots shown on the squares indicate that various ancestors and living people do indeed carry DNA from specific ancestors, even though that’s not the segment that matches a particular person. In other words, the daughter, Ollie, of Joseph Bolton and Margaret Claxton carries 50% pink DNA, represented by the pink dot on blue Ollie Bolton, married to purple William George Estes.

Ollie Bolton and William George Estes had my father, who I’ve shown as half purple (Estes) and half blue (Bolton) because I share Bolton DNA with Match 2, and Estes DNA with Match 1. Obviously, everyone receives half of each parent’s DNA, but in this case, I’m showing the path DNA descended for a specific segment shared with a particular match.

I’ve represented myself with the 5 colors of DNA that I carry from these particular ancestors shown on the pedigree chart. I assuredly will match other people with DNA that we’ve both inherited from these ancestors. I may match these same matches shown with DNA that we both inherited from other ancestors – for example, I might match Match 2 on a different segment that we both inherited from Margaret Claxton. Match 2 is my second cousin, so it’s quite likely that we do indeed share multiple segments of DNA.

Looking at Match 3, who knows very little about their genealogy, I can tell, based on other matches, that we share Dodson DNA inherited through Rutha Dodson.

I need to check every person in my cluster, and that I share DNA with on these same segment addresses to see if they match on my paternal side and if they match each other.

  1. At Family Tree DNA, I will be able to garner more information about whether or not my matches match each other by using the Matrix tool as well as by utilizing Phased Family Matching.

At Family Tree DNA, I determined that these people all match in common with me and Match 1 by using the “In Common With” tool. You can read more about how to use “In Common With” matching, here.

browser paternal.png

Family Matching phases the matches, assigning or bucketed them maternally or paternally (blue and red icons above), indicating, when possible, if these matches occur on the same side of your family. I wrote about the concept of phasing, here, and Phased Family Matching here and here.

Please note that there is no longer a limit on how distantly related a match can be in order to be utilized in Phased Family Matching, so long as it’s over the phase-matching threshold and connected correctly in your tree.

browser family tree dna link tree.png

Bottom line, if you can figure out how you’re related to someone, just add them into your tree by creating a profile card and link their DNA match to them by simply dragging and dropping, as illustrated above.

Linking your matches allows Family Matching to maternally or paternally assign other matches that match both you and your tree-linked matches.

If your matches match you on the same segment on the same parental side, that’s segment triangulation, assuming the matches are IBD. Phased Family Matching does this automatically for you, where possible, based on who you have linked in your tree.

For matches that aren’t automatically bucketed, there’s another tool, the Matrix.

browser matrix.png

In situations where your matches aren’t “bucketed” either maternally or paternally, the Matrix tool allows you to select matches to determine whether your matches also match each other. It’s another way of clustering where you can select specific people to compare. Note that because they also match each other (blue square) does NOT mean it’s on the same segment(s) where they match you. Remember our Venn diagram.

browser matrix grid.png

  1. Just because you and your matches all match each other doesn’t mean that they are matching each other because of the same ancestor. In other words, your matches may match each other due to another or unknown ancestor. In our pedigree example, you can see that the three matches match each other in various ways.
browser pedigree match.png

click to enlarge

  • Match 1 and Match 2 match each other because they are related through the green Jones family, who is not related to me.
  • Match 2 and Match 3 don’t know why they match. They both match me, but not on the same segment they share with each other.
  • Match 1 and Match 3 match through the mustard Dodson line, but not on the same segment that matches me. If we all did match on the same segment, we would be triangulated, but we wouldn’t know why Match 3 was in this triangulation group.
  1. Looking at a downloaded segment file of your matches, available at all testing vendors who support segment information and a chromosome browser, you can’t determine without additional information whether your matches also match each other.

browser chr 15.png

Here’s a group of people, above, that we’ve been working with on chromosome 15.

My entire match-list shows many more matches on that segment of chromosome 15. Below are just a few.

browser chr 15 all

Looking at seven of these people in the chromosome browser, we can see visually that they all overlap on part of a segment on chromosome 15. It’s a lot easier to see the amount of overlap using a browser as opposed to the list. But you can only view 7 at a time in the browser, so the combination of both tools is quite useful. The downloaded spreadsheet shows you who to select to view for any particular segment.

browser chr 15 compare.png

The critical thing to remember is that some matches will be from tyour mother’s side and some from your father’s side.

Without additional information and advanced tools, there’s no way to tell the difference – unless they are bucketed using Phased Family Matching at Family Tree DNA or bracketed with a triangulation bracket at MyHeritage.

At MyHeritage, this assumes you know the shared ancestor of at least one person in the triangulation group which effectively assigns the match to the maternal or paternal side.

Looking at known relatives on either side, and seeing who they also match, is how to determine whether these people match paternally or maternally. In this example below, the blue people are bucketed paternally through Phased Family Matching, the pink maternally, and the white rows aren’t bucketed and therefore require additional evaluation.

browser chr 15 maternal paternal.png

Additional research shows that Jonathan is a maternal match, but Robert and Adam are identical by chance because they don’t match either of my parents on this segment. They might be valid matches on other segments, but not this one.

browser chr 15 compare maternal paternal.png

  1. Utilizing relatives who have tested is a huge benefit, and why we suggest that everyone test their closest upstream relatives (meaning not children or grandchildren.) Testing all siblings is recommended if both parents aren’t available to test, because every child received different parts of their parents’ DNA, so they will match different relatives.

After deleting segments under 7 cM, I combine the segment match download files of multiple family members (who agree to allow me to aggregate their matches into one file for analysis) so that I can create a master match file for a particular family group. Sorting by match name, I can identify people that several of my cousins’ match.

browser 4 groups.png

This example is from a spreadsheet where I’ve combined the results of about 10 collaborating cousins to determine if we can break through a collective brick wall. Sorted by match name, this table shows the first 4 common matches that appear on multiple cousin’s match lists. Remember that how these people match may have nothing to do with our brick wall – or it might.

Note that while the 4 matches, AB, AG, ag, and A. Wayne, appear in different cousins’ match lists, only one shares a common segment of DNA: AB triangulates with Buster and Iona. This is precisely WHY you need segment information, and a chromosome browser, to visualize these matches, and to confirm that they do share a common DNA segment descended from a specific ancestor.

These same people will probably appear in autocluster groups together as well. It’s worth noting, as illustrated in the download example, that it’s much more typical for “in common with” matches to match on different segments than on the same segment. 

  1. Keep in mind that you will match both your mother and father on every single chromosome for the entire length of each chromosome.

browser parent matching.png

Here’s my kit matching with my father, in blue, and mother, in red on chromosomes 1 and 2.

Given that I match both of my parents on the full chromosome, inheriting one copy of my chromosome from each parent, it’s impossible to tell by adding any person at random to the chromosome browser whether they match me maternally or paternally. Furthermore, many people aren’t fortunate enough to have parents available for testing.

To overcome that obstacle, you can compare to known or close relatives. In fact, your close relatives are genetic genealogy gold and serve as your match anchor. A match that matches you and your close relatives can be assigned either maternally or paternally. I wrote about that here.

browser parent plus buster.png

You can see that my cousin Buster matches me on chromosome 15, as do both of my parents, of course. At this point, I can’t tell from this information alone whether Buster matches on my mother’s or father’s side.

I can tell you that indeed, Buster does match my father on this same segment, but what if I don’t have the benefit of my father’s DNA test?

Genealogy tells me that Buster matches me on my paternal side, through Lazarus Estes and Elizabeth Vannoy. Given that Buster is a relatively close family member, I already know how Buster and I are related and that our DNA matches. That knowledge will help me identify and place other relatives in my tree who match us both on the same segment of DNA.

To trigger Phased Family Matching, I placed Buster in the proper place in my tree at Family Tree DNA and linked his DNA. His Y DNA also matches the Estes males, so no adoptions or misattributed parental events have occurred in the direct Estes patrilineal line.

browser family tree dna tree.png

I can confirm this relationship by checking to see if Buster matches known relatives on my father’s side of the family, including my father using the “in common with” tool.

Buster matches my father as well as several other known family members on that side of the family on the same segments of DNA.

browser paternal bucket.png

Note that I have a total of 397 matches in common with Buster, 140 of which have been paternally bucketed, 4 of which are both (my children and grandchildren), and 7 of which are maternal.

Those maternal matches represent an issue. It’s possible that those people are either identical by chance or that we share both a maternal and paternal ancestor. All 7 are relatively low matches, with longest blocks from 9 to 14 cM.

Clearly, with a total of 397 shared matches with Buster, not everyone that I match in common with Buster is assigned to a bucket. In fact, 246 are not. I will need to take a look at this group of people and evaluate them individually, their genealogy, clusters, the matrix, and through the chromosome browser to confirm individual matching segments.

There is no single perfect tool.

Every Segment Tells a Unique History

I need to check each of the 14 segments that I match with Buster because each segment has its own inheritance path and may well track back to different ancestors.

browser buster segments.png

It’s also possible that we have unknown common ancestors due to either adoptions, NPEs, or incorrect genealogy, not in the direct Estes patrilineal line, but someplace in our trees.

browser buster paint.png

The best way to investigate the history and genesis of each segment is by painting matching segments at DNAPainter. My matching segments with Buster are shown painted at DNAPainter, above. I wrote about DNAPainter, here.

browser overlap.png

By expanding each segment to show overlapping segments with other matches that I’ve painted and viewing who we match, we can visually see which ancestors that segment descends from and through.

browser dnapainter walk back.png

These roughly 30 individuals all descend from either Lazarus Estes and Elizabeth Vannoy (grey), Elizabeth’s parents (dark blue), or her grandparents (burgundy) on chromosome 15.

As more people match me (and Buster) on this segment, on my father’s side, perhaps we’ll push this segment back further in time to more distant ancestors. Eventually, we may well be able to break through our end-of-line brick wall using these same segments by looking for common upstream ancestors in our matches’ trees.

Arsenal of Tools

This combined arsenal of tools is incredibly exciting, but they all depend on having segment information available and understanding how to use and interpret segment and chromosome browser match information.

One of mine and Buster’s common segments tracks back to end-of-line James Moore, born about 1720, probably in Virginia, and another to Charles Hickerson born about 1724. It’s rewarding and exciting to be able to confirm these DNA segments to specific ancestors. These discoveries may lead to breaking through those brick walls eventually as more people match who share common ancestors with each other that aren’t in my tree.

This is exactly why we need and utilize segment information in a chromosome browser.

We can infer common ancestors from matches, but we can’t confirm segment descent without specific segment information and a chromosome browser. The best we can do, otherwise, is to presume that a preponderance of evidence and numerous matches equates to confirmation. True or not, we can’t push further back in time without knowing who else matches us on those same segments, and the identity of their common ancestors.

The more evidence we can amass for each ancestor and ancestral couple, the better, including:

  • Matches
  • Shared “In Common With” Matches, available at all vendors.
  • Phased Family Matching at Family Tree DNA assigns matches to maternal or paternal sides based on shared, linked DNA from known relatives.
  • The Matrix, a Family Tree DNA tool to determine if matches also match each other. Tester can select who to compare.
  • ThruLines from Ancestry is based on a DNA match and shared ancestors in trees, but no specific segment information or chromosome browser. I wrote about ThruLines here and here.
  • Theories of Family Relativity, aka TOFR, at MyHeritage, based on shared DNA matches, shared ancestors in trees and trees constructed between matches from various genealogical records and sources. MyHeritage includes a chromosome browser and triangulation tool. I wrote about TOFR here and here.
  • Triangulation available through Phased Family Matching at Family Tree DNA and the integrated triangulation tool at MyHeritage. Triangulation between only 3 people at a time is available at 23andMe, although 23andMe does not support trees. See triangulation article links in the Resource Articles section below.
  • AutoClusters at MyHeritage (cluster functionality included), at Genetic Affairs (autoclusters plus tree reconstruction) and at DNAGedcom (including triangulation).
  • Genealogical information. Please upload your trees to every vendor site.
  • Y DNA and mitochondrial DNA confirmation, when available, through Family Tree DNA. I wrote about the 4 Kinds of DNA for Genetic Genealogy, here and the importance of Y DNA confirmation here, and how not having that information can trip you up.
  • Compiled segment information at DNAPainter allows you to combine segment information from various vendors, paint your maternal and paternal chromosomes, and visually walk segments back in time. Article with DNAPainter instructions is found here.

Autosomal Tool Summary Table

In order to help you determine which tool you need to use, and when, I’ve compiled a summary table of the types of tools and when they are most advantageous. Of course, you’ll need to read and understand about each tool in the sections above. This table serves as a reminder checklist to be sure you’ve actually utilized each relevant tool where and how it’s appropriate.

Family Tree DNA MyHeritage Ancestry 23andMe GedMatch
DNA Matches Yes Yes Yes Yes, but only highest 2000 minus whoever does not opt -in Yes, limited matches for free, more with subscription (Tier 1)
Download DNA Segment Match Spreadsheet Yes Yes No, must use DNAGedcom for any download, and no chromosome segment information Yes Tier 1 required, can only download 1000 through visualization options
Segment Spreadsheet Benefits View all matches and sort by segment, target all people who match on specific segments for chromosome browser View all matches and sort by segment, target all people who match on specific segments for chromosome browser No segment information but matches might transfer elsewhere where segment information is available View up to 2000 matches if matches have opted in. If you have initiated contact with a match, they will not drop off match list. Can download highest 1000 matches, target people who match on specific segments
Spreadsheet Challenges Includes small segments, I delete less than 7cM segments before using No X chromosome included No spreadsheet and no segment information Maximum of 2000 matches, minus those not opted in Download limited to 1000 with Tier 1, download not available without subscription
Chromosome Segment Information Yes Yes No, only total and longest segment, no segment address Yes Yes
Chromosome Browser Yes, requires $19 unlock if transfer Yes, requires $29 unlock or subscription if transfer No Yes Yes, some features require Tier 1 subscription
X Chromosome Included Yes No No Yes Yes, separate
Chromosome Browser Benefit Visual view of 7 or fewer matches Visual view of 7 or fewer matches, triangulation included if ALL people match on same portion of common segment No browser Visual view of 5 or fewer matches Unlimited view of matches, multiple options through comparison tools
Chromosome Browser Challenges Can’t tell whether maternal or paternal matches without additional info if don’t select bucketed matches Can’t tell whether maternal or paternal without additional info if don’t triangulate or you don’t know your common ancestor with at least one person in triangulation group No browser Can’t tell whether maternal or paternal without other information Can’t tell whether maternal or paternal without other information
Shared “In Common With” Matches Yes Yes Yes Yes, if everyone opts in Yes
Triangulation Yes, Phased Family Matching, plus chromosome browser Yes, included in chromosome browser if all people being compared match on that segment No, and no browser Yes, but only for 3 people if “Shared DNA” = Yes on Relatives in Common Yes, through multiple comparison tools
Ability to Know if Matches Match Each Other (also see autoclusters) Yes, through Matrix tool or if match on common bucketed segment through Family Matching Yes, through triangulation tool if all match on common segment No Yes, can compare any person to any other person on your match list Yes, through comparison tool selections
Autoclusters Can select up to 10 people for Matrix grid, also available for entire match list through Genetic Affairs and DNAGedcom which work well Genetic Affairs clustering included free, DNAGedcom has difficulty due to timeouts No, but Genetic Affairs and DNAGedcom work well No, but Genetic Affairs and DNAGedcom work well Yes, Genetic Affairs included in Tier 1 for selected kits, DNAGedcom is in beta
Trees Can upload or create tree. Linking you and relatives who match to tree triggers Phased Family Matching Can upload or create tree. Link yourself and kits you manage assists Theories of Family Relativity Can upload or create tree. Link your DNA to your tree to generate ThruLines. Recent new feature allows linking of DNA matches to tree. No tree support but can provide a link to a tree elsewhere Upload your tree so your matches can view
Matching and Automated Tree Construction of DNA Matches who Share Common Ancestors with You Genetic Affairs for matches with common ancestors with you Not available Genetic Affairs for matches with common ancestors with you No tree support Not available
Matching and Automated Tree Construction for DNA Matches with Common Ancestors with Each Other, But Not With You Genetic Affairs for matches with common ancestors with each other, but not with you Not available Genetic Affairs for matches with common ancestors with each other, but not with you No tree support Not available
DNAPainter Segment Compilation and Painting Yes, bucketed Family Match file can be uploaded which benefits tester immensely. Will be able to paint ethnicity segments soon. Yes No segment info available, encourage your matches to upload elsewhere Yes, and can paint ethnicity segments from 23andMe, Yes, but only for individually copied matches or highest 1000.
Y DNA and Mitochondrial Matching Yes, both, includes multiple tools, deep testing and detailed matching No No No, base haplogroup only, no matching No, haplogroup only if field manually completed by tester when uploading autosomal DNA file

Transfer Your DNA

Transferring your DNA results to each vendor who supports segment information and accepts transfers is not only important, it’s also a great way to extend your testing collar. Every vendor has strengths along with people who are found there and in no other database.

Ancestry does not provide segment information nor a chromosome browser, nor accept uploads, but you have several options to transfer your DNA file for free to other vendors who offer tools.

23andMe does provide a chromosome browser but does not accept uploads. You can download your DNA file and transfer free to other vendors.

I wrote detailed upload/download and transfer instructions for each vendor, here.

Two vendors and one third party support transfers into their systems. The transfers include matching. Basic tools are free, but all vendors charge a minimal fee for unlocking advanced tools, which is significantly less expensive than retesting:

Third-party tools that work with your DNA results include:

All vendors provide different tools and have unique strengths. Be sure that your DNA is working as hard as possible for you by fishing in every pond and utilizing third party tools to their highest potential.

Resource Articles

Explanations and step by step explanations of what you will see and what to do, when you open your DNA results for the first time.

Original article about chromosomes having 2 sides and how they affect genetic genealogy.

This article explains what triangulation is for autosomal DNA.

Why some matches may not be valid, and how to tell the difference.

This article explains the difference between a match group, meaning a group of people who match you, and triangulation, where that group also matches each other. The concepts are sound, but this article relies heavily on spreadsheets, before autocluster tools were available.

Parental phasing means assigning segment matches to either your paternal or maternal side.

Updated, introductory article about triangulation, providing the foundation for a series of articles about how to utilize triangulation at each vendor (FamilyTreeDNA, MyHeritage, 23andMe, GEDmatch, DNAPainter) that supports triangulation.

These articles step you through triangulation at each vendor.

DNAPainter facilitates painting maternally and paternally phased, bucketed matches from FamilyTreeDNA, a method of triangulation.

Compiled articles with instructions and ideas for using DNAPainter.

Autoclustering tool instructions.

How and why The Leeds Method works.

Step by step instructions for when and how to use FamilyTreeDNA’s chromosome browser.

Close family members are the key to verifying matches and identifying common ancestors.

This article details how much DNA specific relationships between people can expect to share.

Overview of transfer information and links to instruction articles for each vendor, below.

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Disclosure

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Products and Services

Genealogy Research

Fun DNA Stuff

  • Celebrate DNA – customized DNA themed t-shirts, bags, and other items

Shared cM Project 2020 Analysis, Comparison & Handy Reference Charts

Recently, Blaine Bettinger published V4 of the Shared cM Project, and along with that, Jonny Perl at DNAPainter updated the associated interactive tool as well, including histograms. I wrote about that, here.

The goal of the shared cM project was and remains to document how much DNA can be expected to be shared by various individuals at specific relationship levels. This information allows matches to at least minimally “position” themselves in a general location their trees or conversely, to eliminate specific potential relationships.

Shared cM Project match data is gathered by testers submitting their match information through the submission portal, here.

When the Shared cM Project V3 was released in September 2017, I combined information from various sources and provided an analysis of that data, including the changes from the V2 release in 2016.

I’ve done the same thing this year, adding the new data to the previous release’s table.

Compiled Comparison Table

I initially compiled this table for myself, then decided to update it and share with my readers. This chart allows me to view various perspectives on shared data and relationships and in essence has all the data I might need, including multiple versions, in one place. Feel free to copy and save the table.

In the comparison table below, the relationship rows with data from various sources is shown as follows:

  • White – Shared cM Project 2016
  • Peach – Shared cM Project 2017
  • Purple – Shared cM Project 2020
  • Green – DNA Detectives chart

I don’t know if DNA Detectives still uses the “green chart” or if they have moved to the interactive DNAPainter tool. I’ve retained the numbers for historical reference regardless.

Additionally, in some places, you’ll see references to the “degree of relationship,” as in “third degree relatives always match each other.” I’ve included a “Degree of Relationship” column to the far right, but I don’t come across those “relationship degree” references often anymore either. However, it’s here for reference if you need it.

23andMe still gives relationships in percentages, so I’ve included the expected shared percent of DNA for each relationship and the actual shared range from the DNA Detectives Green Chart.

One column shows the expected shared cM amount, assuming that 50% of the DNA from each ancestor is passed on in each generation. Clearly, we know that inheritance doesn’t happen that cleanly because recombination is a random event and children do NOT inherit exactly half of each ancestor’s DNA carried by their parents, but the average should be someplace close to this number.

shared cm table 2020

click to open separately, then use your magnifier to enlarge

The first thing I noticed about V4 is that there is a LOT more data which means that the results are likely more accurate. V4 increased by 32K data points, or 147%. Bravo to everyone who participated, to Blaine for the analysis and to Jonny for automating the results at DNAPainter.

Methods

Blaine provided his white paper, here, which includes “everything you need to know” about the project, and I strongly encourage you to read it. Not only does this document explain the process and methods, it’s educational in its own right.

On the first page, Blaine discusses issues. Any time you are crowd sourcing information, you’re going to encounter challenges and errors. Blaine did remove any entries that were clearly problematic, plus an additional 1% of all entries for each category – .5% from each end meaning the largest and smallest entries. This was done in an attempt to remove the results most likely to be erroneous.

Known issues include:

  • Data entry errors – I refer to these as “clerical mutations,” but they happen and there is no way, unless the error is egregious, to know what is a typo and what is real. Obviously, a parent sharing only a 10 cM segment with a child is not possible, but other data entry errors are well within the realm of possible.
  • Incorrect relationships – Misreported or misunderstood relationships will skew the numbers. Relationships may be believed to be one type, but are actually something else. For example, a half vs full sibling, or a half vs full aunt or uncle.
  • Misunderstood Relationships – People sometimes become confused as to the difference between “half” and “removed” from time to time. I wrote a helpful article titled Quick Tip – Calculating Cousin Relationships Easily.
  • Endogamy – Endogamy occurs when a population intermarries within itself, meaning that the same ancestral DNA is present in many members of the community. This genetic result is that you may share more DNA with those cousins than you would otherwise share with cousins at the same distance without endogamy.
  • Pedigree Collapse – Pedigree collapse occurs when you find the same ancestors multiple times in your tree. The closer to current those ancestors appear, the more DNA you will potentially carry from those repeat ancestors. The difference between endogamy and pedigree collapse is that endogamy is a community event and pedigree collapse has only to do with your own tree. You might just have both, too.
  • Company Reporting Differences – Different companies report DNA in different ways in addition to having different matching thresholds. For example, Family Tree DNA includes in your match total all DNA to 1 cM that you share with a match over the matching threshold. Conversely, Ancestry has a lower matching threshold, but often strips out some matching DNA using Timber. 23andMe counts fully identical segments twice and reports the X chromosome in their totals. MyHeritage does not report the X chromosome. There is no “right” or “wrong,” or standardization, simply different approaches. Hopefully, the variances will be removed or smoothed in the averages.
  • Distant Cousin Relationships – While this isn’t really an issue, per se, it’s important to understand what is being reported beyond 2nd cousin relationships in that the only relationships used to calculate these averages is the DNA from people who DO share DNA with their more distant cousins. In other words, if you do NOT match your 3rd cousin, then your “0” shared DNA is not included in the average. Only those who do match have their matching amounts included. This means that the average is only the average of people who match, not the average of all 3rd cousins.

Challenges aside, the Shared cM Project provides genealogists with a wonderful opportunity to use the combined data of tens of thousands of relationships to estimate and better understand the relationship range of our matches.

The Shared cM Project in combination with DNAPainter provides us with a wonderful tool.

Histograms

When analyzing the data, one of the first things I noticed was a very unusual entry for parent/child relationships.

We all know that children each inherit exactly half of their parent’s DNA. We expect to find an amount in the ballpark of 3400, give or take a bit for normal variances like read errors or reporting differences.

Shared cM parent child.png

click to enlarge

I did not expect to see a minimum shared cM amount for a child/parent relationship at 2376, fully 1024 cM below expected value of 3400 cM. Put bluntly, that’s simply not possible. You cannot live without one third of one of your parent’s DNA. If this data is actually accurate from someone’s account, please contact me because I want to actually see this phenomenon.

I reached out to Blaine, knowing this result is not actually possible, wondering how this would ever get through the quality control cycle at any vendor.

After some discussion, here’s Blaine’s reply:

If you look at the histogram, you’ll see that those are most likely outliers. One of my lessons for the ScP (Shared cM Project) lately is that people shouldn’t be using the data without the histograms.

People get frustrated with this, but I can’t edit data without a basis even if I think it doesn’t make sense. I have to let the data itself decide what data to remove. So I removed 1% from each relationship, the lowest 0.5% and the highest 0.5%. I could have removed more, but based on the histograms, [removing] more appeared to be removing too much valid data. As people submit more parent/child relationships these outliers/incorrect submissions will be removed. But thankfully using the histograms makes it clear.

Indeed, if you look on page 23 on Blaine’s white paper, you’ll see the following histogram of parent/child relationships submitted.

shared cm histogram.png

click to enlarge

Keep in mind that Blaine already removed any obvious errors, plus 1% of the total from either end of the spectrum. In this case, he utilized 2412 submissions, so he would have removed about 24 entries that were even further out on the data spectrum.

On the chart above, we can see that a total of about 14 are still really questionable. It’s not until we get to 3300 that these entries seem feasible. My speculation is that these people meant to type 3400 instead of 2400, and so forth.

shared cm parent grid.png

click to enlarge

The great news is that Jonny Perl at DNAPainter included the histograms so you can judge for yourself if you are in the weeds on the outlier scale by clicking on the relationship.

shared cm parent submissions.png

click to enlarge

Other relationships, like this niece/nephew relationship fit the expected bell shaped curve very nicely.

shared cm niece.png

Of course, this means that if you match your niece or nephew at 900 cM instead of the range shown above, that person is probably not your full niece or nephew – a revelation that may be difficult because of the implications for you, your parent and sibling. This would suggest that your sibling is a half sibling, not a full sibling.

Entering specific amounts of shared DNA and outputting probabilities of specific relationships is where the power of DNAPainter enters the picture. Let’s enter 900 cM and see what happens.

shared cm half niece.png

That 900 cM match is likely your half niece or nephew. Of course, this example illustrates perfectly why some relationships are entered incorrectly – especially if you don’t know that your niece or nephew is a half niece or nephew – because your sibling is a half-sibling instead of a full sibling. Some people, even after receiving results don’t realize there is a discrepancy, either because their data is on the boundary, with various relationships being possible, or because they don’t understand or internalize the genetic message.

shared cm full siblings.png

click to enlarge

This phenomenon probably explains the low minimum value for full siblings, because many of those full siblings aren’t. Let’s enter 1613 and see what DNAPainter says.

shared cm half sibling.png

You’ll notice that DNAPainter shows the 1613 cM relationship as a half-sibling.

shared cm sibling.png

And the histogram indeed shows that 1613 would be the outlier. Being larger that 1600, it would appear in the 1700 category.

shared cm half vs full.png

click to enlarge

Accurately discerning close relationships is often incredibly important to testers. In the histogram chart above, you can see that the blue and orange histograms plotted on the same chart show that there is only a very small amount of overlap between the two histograms. This suggests that some people, those in the overlap range, who believe they are full siblings are in reality half-siblings, and possibly, a few in the reverse situation as well.

What Else is Noteworthy?

First, some relationships cannot be differentiated or sorted out by using the cM data or histogram charts alone.

shared cm half vs aunt.png

click to enlarge

For example, you cannot tell the difference between half-siblings and an aunt/uncle relationship. In order to make that determination, you would need to either test or compare to additional people or use other clues such as genealogical research or geographic proximity.

Second, the ranges of many relationships are wider than they were before. Often, we see the lows being lower and the highs being higher as a result of more data.

shared cm low high.png

click to enlarge

For example, take a look at grandparents. The expected relationship is 1700 cM, the average is 1754 which is very close to the previous average numbers of 1765 and 1766. However, the minimum is now 984 and the new maximum is 2462.

Why might this be? Are ranges actually wider?

Blaine removed 1% each time, which means that in V3, 6 results would have been removed, 3 from each end, while 11 would be removed in V4. More data means that we are likely to see more outliers as entries increase, with the relationship ranges are increasingly likely to overlap on the minimum and maximum ends.

Third, it’s worth noting that several relationships share an expected amount of DNA that is equal, 12.5% which equals 850 cM, in this example.

shared cm 4 relationships.png

click to enlarge

These four relationships appear to be exactly the same, genetically. The only way to tell which one of these relationships is accurate for a given match pair, aside from age (sometimes) and opportunity, is to look at another known relationship. For example, how closely might the tester be related to a parent, sibling, aunt, uncle or first cousin, or one of their other matches. Occasionally, an X chromosome match will be enlightening as well, given the unique inheritance path of the X chromosome.

Additional known relationships help narrow unknown relationships, as might Y DNA or mitochondrial DNA testing, if appropriate. You can read about who can test for the various kinds of tests, here.

Fourth, it’s been believed for several years that all 5th degree relatives, and above, match, and the V4 data confirms that.

shared cm 5th degree.png

click to enlarge

There are no zeroes in the column for minimum DNA shared, 4th column from right.

5th degree relatives include:

  • 2nd cousins
  • 1st cousins twice removed
  • Half first cousins once removed
  • Half great-aunt/uncle

Fifth, some of your more distant cousins won’t match you, beginning with 6th degree relationships.

shared cm disagree.png

click to enlarge

At the 6th degree level, the following relationships may share no DNA above the vendor matching threshold:

  • First cousins three times removed
  • Half first cousins twice removed
  • Half second cousins
  • Second cousins once removed

You’ll notice that the various reporting models and versions don’t always agree, with earlier versions of the Shared cM Project showing zeroes in the minimum amount of DNA shared.

Sixth, at the 7th degree level, some number of people in every relationship class don’t share DNA, as indicated by the zeros in the Shared cM Minimum column.

shared cm 7th degree.png

click to enlarge

The more generations back in time that you move, the fewer cousins can be expected to match.

shared cm isogg cousin match.png

This chart from the ISOGG Wiki Cousin statistics page shows the probability of matching a cousin at a specific level based on information provided by testing companies.

Quick Reference Chart Summary

In summary, V4 of the Shared cM Project confirms that all 2nd cousins can expect to match, but beyond that in your trees, cousins may or may not match. I suspect, without evidence, that the further back in time that people are related, the less likely that the proper “cousinship level” is reported. For example, it would be easier to confuse 7th and 8th cousins as compared to 1st and 2nd cousins. Some people also confuse 8th cousins with 8 generations back in your tree. It’s not equivalent.

shared cm eighth cousin.png

click to enlarge

It’s interesting to note that Degree 17 relatives, 8th cousins, 9 generations removed from each other (counting your parents as generation 1), still match in some cases. Note that some companies and people count you as generation 1, while others count your parents as generation 1.

The estimates of autosomal matching reaching 5 or 6 generations back in time, meaning descendants of common 4 times great-grandparents will sometimes match, is accurate as far as it goes, although 5-6 generations is certainly not a line in the sand.

It would be more accurate to state that:

  • 2nd cousins, people descended from common great-grandparents, 3 generations back in time will always match
  • 4th cousins, people descended from common 3 times great grandparents, 5 generations back in time, will match about half of the time
  • 8th cousins, people descended from 7 times great grandparents, 9 generations back in time still match a small percentage of the time
  • Cousins from more distant ancestors can possibly match, but it’s unlikely and may result from a more recent unknown ancestor

I created this summary chart, combining information from the ISOGG chart and the Shared cM Project as a handy quick reference. Enjoy!

shared cm quick reference.png

click to enlarge

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Disclosure

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Products and Services

Genealogy Research

Fun DNA Stuff

  • Celebrate DNA – customized DNA themed t-shirts, bags and other items

Triangulation in Action at DNAPainter

Recently, I published the article, Hitting a Genealogy Home Run Using Your Double-Sided Two-Faced Chromosomes While Avoiding Imposters. The “Home Run” article explains why you want to use a chromosome browser, what you’re seeing and what it means to you.

This article, and the rest in the “Triangulation in Action” series introduces triangulation at FamilyTreeDNA, MyHeritage, 23andMe, GedMatch and DNAPainter, explaining how to use triangulation to confirm descent from a common ancestor. You may want to read the introductory article first.

This first section, “What is Triangulation” is a generic tutorial. If you don’t need the tutorial, skip to the “Transfers” or “Triangulation at DNAPainter” section.

What is Triangulation?

Think of triangulation as a three-legged stool – a triangle. Triangulation requires three things:

  1. At least three (not closely related) people must match
  2. On the same reasonably sized segment of DNA and
  3. Descend from a common ancestor

Triangulation is the foundation of confirming descent from a common ancestor, and thereby assigning a specific segment to that ancestor. Without triangulation, you might just have a match to someone else by chance. You can confirm mathematical triangulation, numbers 1 and 2, above, without knowing the identity of the common ancestor.

Reasonably sized segments are generally considered to be 7cM or above on chromosomes 1-22 and 15cM or above for the X chromosome.

Boundaries

Triangulation means that all three, or more, people much match on a common segment. However, what you’re likely to see is that some people don’t match on the entire segment, meaning more or less than others as demonstrated in the following examples.

FTDNA Triangulation boundaries

You can see that I match 5 different cousins who I know descend from my father’s side on chromosome 15 above. “I” am the grey background against which everyone else is being compared.

I triangulate with these matches in different ways, forming multiple triangulation groups that I’ve discussed individually, below.

Triangulation Group 1

FTDNA triangulation 1

Group 1 – On the left group of matches, above, I triangulate with the blue, red and orange person on the amount of DNA that is common between all of them, shown in the black box. This is triangulation group 1.

Triangulation Group 2

FTDNA triangulation 2

Group 2 – However, if you look just at the blue and orange triangulated matches bracketed in green, I triangulate on slightly more. This group excludes the red person because their beginning point is not the same, or even close. This is triangulation group 2.

Triangulation Group 3 and 4

FTDNA triang 3

Group 3 – In the right group of matches, there are two large triangulation groups. Triangulation group 3 includes the common portions of blue, red, teal and orange matches.

Group 4 – Triangulation group 4 is the skinny group at right and includes the common portion of the blue, teal and dark blue matches.

Triangulation Groups 5 and 6

FTDNA triang 5

Group 5 – There are also two more triangulation groups. The larger green bracketed group includes only the blue and teal people because their end locations are to the right of the end locations of the red and orange matches. This is triangulation group 5.

Group 6 – The smaller green bracketed group includes only the blue and teal person because their start locations are before the dark blue person. This is triangulation group 6.

There’s actually one more triangulation group. Can you see it?

Triangulation Group 7

FTDNA triang 7

Group 7 – The tan group includes the red, teal and orange matches but only the areas where they all overlap. This excludes the top blue match because their start location is different. Triangulation group 7 only extends to the end of the red and orange matches, because those are the same locations, while the teal match extends further to the right. That extension is excluded, of course.

Slight Variations

Matches with only slight start and end differences are probably descended from the same ancestor, but we can’t say that for sure (at this point) so we only include actual mathematically matching segments in a triangulation group.

You can see that triangulation groups often overlap because group members share more or less DNA with each other. Normally we don’t bother to number the groups – we just look at the alignment. I numbered them for illustration purposes.

Shared or In-Common-With Matching

Triangulation is not the same thing as a 3-way shared “in-common-with” match. You may share DNA with those two people, but on entirely different segments from entirely different ancestors. If those other two people match each other, it can be on a segment where you don’t match either of them, and thanks to an ancestor that they share who isn’t in your line at all. Shared matches are a great hint, especially in addition to other information, but shared matches don’t necessarily mean triangulation although it’s a great place to start looking.

I have shared matches where I match one person on my maternal side, one on my paternal side, and they match each other through a completely different ancestor on an entirely different segment. However, we don’t triangulate because we don’t all match each other on the SAME segment of DNA. Yes, it can be confusing.

Just remember, each of your segments, and matches, has its own individual history.

Imputation Can Affect Matching

Over the years the chips on which our DNA is processed at the vendors have changed. Each new generation of chips tests a different number of markers, and sometimes different markers – with the overlaps between the entire suite of chips being less than optimal.

I can verify that most vendors use imputation to level the playing field, and even though two vendors have never verified that fact, I’m relatively certain that they all do. That’s the only way they could match to their own prior “only somewhat compatible” chip versions.

The net-net of this is that you may see some differences in matching segments at different vendors, even when you’re comparing the same people. Imputation generally “fills in the blanks,” but doesn’t create large swatches of non-existent DNA. I wrote about the concept of imputation here.

What I’d like for you to take away from this discussion is to be focused on the big picture – if and how people triangulate which is the function important to genealogy. Not if the start and end segments are exactly the same.

Triangulation Solutions

All vendors except Ancestry offer some type of triangulation.

If you and your Ancestry matches have uploaded to GedMatch, Family Tree DNA or MyHeritage, you can triangulate with them there. Otherwise, you can’t triangulate Ancestry results, so encourage your Ancestry matches to transfer.

I wrote more specifically about triangulation here and here.

Transfer your results in order to obtain the maximum number of matches possible. Every vendor has people in their data base that haven’t tested elsewhere.

Transfers

Have you tested family members, especially everyone in the older generations? You can transfer their kits from Ancestry or 23andMe if they’ve tested there to FamilyTreeDNA, MyHeritage and GedMatch.

Here’s how to transfer:

Now that we’ve reviewed triangulation at each vendor; FamilyTreeDNA, MyHeritage, 23andMe and GedMatch, let’s looking at utilizing triangulation at DNAPainter.

Triangulation at DNAPainter

Once you identify your ancestral segments with matches, or using triangulation, you can paint them on your maternal or paternal chromosomes utilizing DNAPainter.

The great aspect of DNAPainter is that you don’t have to triangulate in order to use DNAPainter. Just identifying matches as maternal or paternal allows you to visually see where on your maternal or paternal chromosomes your matches fall, in essence triangulating groups for you.

DNAPainter assigns colors to each ancestor and shows your match names, which I’ve disabled in this example for privacy. I’ve also optionally painted my ethnicity segments from 23andMe, which I discussed in this article.

Triangulation DNAPainter chr 22.png

Above, on chromosome 22, I’ve painted matches that I know descend from either my mother’s (pink) or father’s (blue) side. At DNAPainter, I DO have both a maternal and paternal chromosome, but they are only useful AFTER I figure out which side of my family a match comes from, or if I paint my Family Matching bucketed maternal and paternal matches in an upload file from Family Tree DNA. I wrote instructions for how to do that, here. The combination of Family Matching and DNAPainter is awesome!

Looking at the graphic above, I know that three separate people who match me descend from the bright pink ancestor on my maternal chromosome; Curtis Lore and his wife. I’ve assigned Curtis the bright pink color, and now every match that I paint assigned to Curtis and his wife is colored pink.

One person descends from Curtis’s parents, Anthony Lore and his wife Rachel Hill who I’ve assigned as green.

Until someone else matches me and descends either from Anthony Lore’s parents or Rachel Hill’s parents on this green segment, I won’t know which of those two ancestors, or both, provided (pieces of) that segment to me.

Anthony Lore and Rachel Hill are my great-great-grandparents and Curtis Lore is their son. Even if I only have 2 matches on this segment, one pink and one green, I would know that the green portion of my maternal chromosome 22 is attributed to Anthony and Rachel which means I inherited that green segment from my pink ancestor, Curtis Lore.

In order to determine the source of the two pink triangulated matches at far right, I’ll need to wait until someone from either Curtis’s line or his wife Nora Kirsch’s line match me on that same segment.

We build these groups of triangulated segments slowly, creating in essence a timeline on our chromosomes. It seems like it’s taking forever, but four generations distance with 2 separate triangulated segments really isn’t bad at all!

At DNAPainter, triangulation is as simple as painting your identified matches, either individually, one by one, or using the group import features. I would only recommend utilizing that feature at Family Tree DNA where their Family Matching software divides your matches into maternal and paternal, allowing DNAPainter to paint them on the correct chromosome. Otherwise, the segments are painted, but you can’t tell which side, maternal or paternal, they come from, so I don’t find painting all matches useful without some way to differentiate between maternal and paternal. After all, the point and power of a chromosome browser is to determine how each person is related, from which side, and from which ancestor.

In the article, DNAPainter Instructions and Resources, I compiled my various articles about the many ways to use DNAPainter, including an introduction.

Transfer

Be sure to test at or transfer to each vendor who provides segment information. Unfortunately, Ancestry does not, but you can transfer your ancestry results to Family Tree DNA, MyHeritage and GedMatch, each of which has unique features that the others don’t have. Transferring and matching is free at each vendor.

I wrote transfer instructions for each vendor, here.

Then, paint and triangulate all in one step at DNAPainter.

Have fun!

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Disclosure

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Services

Genealogy Research