Utilizing MyHeritage AutoClusters to Analyze your DNA Matches

AutoClusters are so much fun and can provide tons of information. I’m going to step through how to analyze your cluster matches easily and productively in conjunction with the MyHeritage tools, but first, a little light housekeeping.

First, please note that this article was presented as a webinar for MyHeritage as part of the MyHeritageDNA Facebook LIVE series. You can watch it anytime, free, at the permanent link, here, courtesy of MyHeritage and me. However, everyone learns differently, and some people do better with written instructions. You can follow the step-by-step instructions in this article.

Second, AutoClusters are a built-in advanced DNA tool at MyHeritage for customers who either:

I would encourage the subscription because many of the MyHeritage tools function best with a large tree. While MyHeritage does offer free trees of up to 250 people, to take full advantage of your DNA test plus tools, you’ll want a larger tree. Subscription features and pricing can be found here and you can try a free trial subscription here.

Third, if you’d like to transfer your DNA file from another vendor, I wrote step-by-step instructions, here.

Fourth, MyHeritage is having a $49 Halloween DNA sale, here, with free shipping if you purchase 2 kits.

And last, Genetic Affairs, the author of AutoClusters, provides additional functionality on their own website for use with FamilyTreeDNA and 23andMe. Customers at Genetic Affairs cannot access MyHeritage data from the Genetic Affairs website since MyHeritage contracts with Genetic Affairs to provide AutoClusters directly to MyHeritage customers at no additional charge. I only mention this because the functionality described in this article and in the companion webinar discusses the functionality by using a combination of AutoClusters and the unique tools available only at MyHeritage.

Ok, housekeeping complete – on to AutoClusters!

Get yourself a cup of coffee or tea. We’re taking a deep dive here, beginning to end, but keep in mind that you don’t have to do everything that’s possible initially, or ever. It’s OK to take baby steps. Just know that AutoClusters can be a superpower to breaking down brick walls. Not only that, AutoClusters are simply FUN!

Let’s start with a basic question.

What is an AutoCluster and Why Do I Care?

An AutoCluster is an artful bouquet of hints, arranged by family group in a puzzle format.

AutoCluster technology, a form of genetic networks, is a way to display your matches who match you and who also match each other in a meaningful, colored-coded group. Each group, or cluster, shares a common ancestral line, somehow. That “how” discovery, or better stated, “which ancestor” discovery is up to you – but clusters provide huge hints!

We’re genealogists, right – we live for hints. Let’s take a look at how this works.

I would suggest reading through this article the first time, then working through the steps as you read it a second time with your own AutoCluster. Don’t worry, I’ll show you how to request one.

This example of my own AutoCluster report, which I’ll be using throughout this article, shows three different clusters.

Everyone within a cluster matches you, but not everyone matches each other. Each cluster is represented by colored cells, each of which represent the intersection of two people who match each other. In the third yellow cluster, everyone matches each other except for two people who don’t match each other.

Grey cells fall into both of the two clusters they are between. For example, the grey cells to the right of the red cluster in the red box match people in both the first red and second tan cluster.

What this means is that once you’ve identified the genesis of each cluster, you know that people who are grey members of both clusters descend from both lines which could represent the two people in an ancestor couple. In my tree, my maternal great-grandfather Joseph Bolton married Margaret Claxton/Clarkson, and I expect the grey people descend from this couple or from both lines individually. One way or another, they match people from both clusters.

The grey people are an additional hint – so don’t neglect them. In fact, some of these grey squares can be even more important that people within clusters because they span two clusters.

Ok, so how do I generate an AutoCluster at MyHeritage?

Requesting an AutoCluster

You’ll find the AutoCluster featured under the DNA menu, under DNA Tools.

Click “Explore.”

If you manage multiple kits, be sure to select the right kit for the right person.

In my case, I have a transfer kit, then I tested at MyHeritage for the health product, so I have two kits. A MyHeritage kit shows with the MH prefix, while a transfer kit shows a different prefix.

The matches and AutoClusters are slightly different between the two kits because the tests are run on different DNA chips.

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After selecting the correct kit, just click on the purple “Generate” button. Note that if your parents have tested, generating an AutoCluster for one or both of them will help you immensely with your own AutoCluster. If both of your parents have tested, you may want to work only with their AutoCluster reports, and not your own. They will have people in their clusters that you don’t because you didn’t inherit that particular piece of DNA from your parents.

Next, you’ll see a message informing you that your AutoCluster is being generated and will be sent to the email registered to your account.

Queue up Jeopardy countdown thinking music

Just a few minutes later, my AutoCluster arrived in my email box. (Note – check your spam folder.)

If you request multiple AutoClusters for different tests or accounts at the same time, take care not to mix them up. Voice of experience here…

You’ll receive 3 items in zip file. I save my files to my computer.

  • Readme file
  • HTML (with the colored circle)
  • Spreadsheet which is a different format of the html file

I don’t know how well the HTML file and the spreadsheet will display on non-computer devices, although I know the HTML file does display on an iPad. I generally work from my computer.

The HTML File

Just click on the HTML file to display your AutoClusters. You’ll get to enjoy seeing them “flying into place,” assembling into clusters. I told you these were fun!

You can play around a bit with options, but “cluster” is the default view and the only one we’re covering in this article.

Each colored cluster is a group of interrelated matches.

I have a total of 18 clusters.

Scroll towards the bottom to view the parameters used to generate the clusters.

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These parameters are not adjustable and have been optimized by MyHeritage to perform well for all customers, including testers with significant endogamy, such as people with Jewish heritage. At the system-generated threshold, I have 100 qualifying matches. Note that the system optimizes the thresholds individually for each person, and your thresholds might be slightly different than mine.

  • Min threshold 40 cM (often this level of match is in the 5C or more distant range)
  • Max threshold 350 cM (closer than 350 would probably be 1C or closer)
  • Shared DNA match minimum threshold 15 cM (overlap of matching DNA)

You’re probably wondering – where are the highest matches such as parents, siblings, uncles, aunts, etc.?

Close family members would be in many clusters. Placing one person into more than two clusters is simply not technically possible due to the constraints of a two-dimensional grid medium, so close family matches are excluded from clusters as to not be confusing. You can still use close family members in shared matching. In fact, they are extremely useful and we will discuss that shortly.

Fly your cursor over the cluster to view the cluster members and their match status to each other. In the grid, each person who matches another has a colored cell. In this example, my cursor is pointing to the cell where “cro” matches Bonnie. Names are obscured for privacy.

Scroll on down below the cluster box to view additional information about each member of the cluster. Many people don’t realize there’s more because they are excited about viewing their clusters and miss this important information about the cluster members beneath the grid.

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Your notes are critically important and you can search by notes. When I identify how someone is related to me, or even clues, I record that information in the notes. I SHOULD have recorded “TOFR” for the matches who have Theories of Family Relativity, and I have gone back and done that now. We’ll talk about TOFRs in a minute.

You may be able to identify the common line or ancestral couple based on the matches alone. Note that these matches may not all be from the same generation. For example, I have some matches in this group who descend from various Claxton ancestors, spanning at least 4 generations. That commonality is how I know the cluster is “Claxton/Clarkson” and not from one of their wives – at least to the most distant generation where I’m stuck.

Matches can span many generations in a “line” and probably involve multiple DNA segments, especially in larger clusters.

Click on “Tree” to view the tree of your match.

Click on “Name” to review their DNA match with you.

Note that your match may match you on more than one line and possibly on both parents’ sides. Inclusion in this cluster simply tells you they match on this line and does not eliminate any other lines.

Now, let’s begin our cluster analysis and drill down.

Select the Best Match

I always begin my analysis with what I think is the “best” match in a cluster.

  • Best could be the largest tree.
  • Best could be the largest match.
  • Best could be the largest number of ICW (in common with) cluster matches.
  • Best is any match with a TOFR (Theory of Family Relativity)

I make notes for all TOFR matches, after verifying, of course, indicating the common ancestors. I also note “TOFR” so I know, when looking at clusters, why I assigned that specific ancestor. When you have a TOFR, MyHeritage has already done the heavy lifting for you.

I note matches’ inclusion in a cluster to remind me to check those clustered matches first. When a match is in a cluster, AutoCluster has done the heavy lifting for you.

The key to success is to utilize multiple tools, together.

Like what?

The Success Triumvirate

Successfully identifying clusters, ancestors and how each person matches you is accomplished through a combination of three primary tools. I call this the “Success Triumvirate” because the three are quite interwoven.

We are going to use all three of these tools, together, so let’s talk about them individually briefly.

Theories of Family Relativity (TOFR)

TOFRs are super hints – theories about which common ancestors your matches share with you.

I wrote about Theories of Family Relativity complete with step-by-step instructions:

TOFRs connect you to your DNA matches by identifying a potential ancestor through a succession of trees and documents from different sources. You can do a number of things to help TOFRs, (and yourself), along.

  • TOFR formation requires a tree, so create one at MyHeritage, using their free TreeBuilder on your computer, or upload a tree that you’ve already created elsewhere.
  • TOFR does best if you complete the tree through grandchildren of each ancestor, at least, if possible, for each generation. Think of each person as a hand reaching out to latch on to the same person in another person’s tree. The more hands, the better your odds of success.
  • Include birth/death date and location, or as much as you know.
  • Accept Smart Matches where appropriate.
  • Make notes. Notes keep you from retracing your own steps.

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A TOFR connection as offered by MyHeritage may not be exactly accurate, but the common ancestor may be accurately identified anyway. For example, in the above TOFR, Margaret Claxton did not marry William Luke Monday, her sister did. The TOFR isn’t exactly correct, but the common ancestors are easily identified. I can take it from this point – no problem.

Always check to see if multiple TOFR paths exist because important hints may be hidden in those links. Think of yourself as a sleuth😊

Let’s take a look at one cousin in this Claxton cluster, Bonnie. What can we learn, and how? Let’s review Bonnie’s DNA match to me.

Reviewing Bonnie’s DNA Match

Clicking on “Review DNA Match” with Bonnie shows me a host of information divided into sections, beginning with a TOFR.

Bonnie Has a TOFR – Hot Diggity!

The first thing we see is that Bonnie does have a TOFR with the tester (me), so we can identify a potential common ancestor.

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Not only that, but Bonnie has a fairly robust tree of 4043 people, so she must be interested in genealogy at some level.

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Not only that, but there are two separate potential “paths” that connect me and Bonnie at a potential common ancestor. One may be more accurate than the other. Be sure to check all paths.

I can click on the little green dots that bridge trees by connecting what the system believes to be the same ancestor to view and evaluate that information.

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Clicking on this green dot would display the match criteria from both trees.

In this case, the weighted match was 76%. The information for Margaret herself was mostly the same, but her husband(s) and children were different due to the inaccuracy of showing her married to her brother-in-law.

Evaluate all TOFRs, links, trees and hints for accuracy. They aren’t gospel.

Another great source of hints is Smart Matches. You may, and probably will, have Smart Matches with people’s trees who are not DNA matches to you. Smart Matches are not necessarily connected to DNA matches specifically, but they do help TOFR form accurately.

Bonnie Has Smart Matches!

MyHeritage generates Smart Matches WITHOUT factoring in genetic matching. Smart Matches occur when enough common factors exist between a person in your tree and a person in another tree whether you are a DNA match with that person or not.

If you have Smart Matches with a DNA match, they will be listed when you review your DNA match with that person.

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To determine whether or not this Smart Match could be relevant to your DNA autocluster, be sure to notice whether this is a direct ancestor of both people. To be relevant to DNA, the Smart Match must be for a direct ancestor or at least lead to a direct ancestor.

Next, click “Review Smart Match.”

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The first thing you’re going to see is “Confirm Match,” and as a genealogist, that stopped me dead in my tracks.

That’s skull-and-crossbones frightening. I don’t know what “confirm match” means or does? Does it mean that all of their information will automatically be copied to my tree if I click that button? I certainly DON’T WANT THAT!!!

I may not want the “Improved Info” either. That information may not actually be improved. What do I do?

For a long time, I did nothing because I didn’t want to mess something up – but doing nothing isn’t the right answer either – because confirming Smart Matches helps TOFRs for everyone.

I wish MyHeritage provided a bit more information here, because “Confirm Match” doesn’t import any information into your tree automatically. You have the opportunity to review everything first.

There are two questions at this point you need to ask and answer independently:

  1. Is this the same person?
  2. If so, do I want any of this data to be imported to my tree?

If it IS the same person, go ahead and confirm – you’ll get to review each new or “improved” item at that point.

If it’s NOT the same person, scroll to the bottom of the page and reject the match.

In this example, Nicholas Speak is the same person, so I’ve clicked on “Confirm Match” which then allows me to review each piece of information that is different, individually. If I want to import that information into my tree, I click on the little arrow to bring the information into my tree, replacing mine. If I do nothing, no information is copied to my tree. It’s that simple. If I make a mistake, I can always edit my own information.

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Bonnie Has Shared Ancestral Surnames!

Another hint for DNA matches is “Shared Ancestral Surnames.” If you can’t figure out how you are related, take a look at these. Of course, Smith is extremely common, but groups of shared surnames are a huge hint, especially if you also have shared locations.

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You may discover more than one line that connects you to this tester – which sometimes makes things a little more complicated! That’s when location can become a life-saver.

Bonnie Has Shared Ancestral Places!

Shared ancestral places can be very useful, even if you can’t identify common surnames, especially in cases where surnames may not be useful. Unknown parent events and adoptions have always occurred, and a specific location may go a long way in terms of identifying the ancestors of both parties that may be related.

Purple pins with numbers mean you BOTH have ancestors from that location. Bonnie and I share 65 ancestors from one place. I definitely need to evaluate that location!

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Clicking on Tennessee shows the pins in that location. Clicking on a specific pin displays the ancestors from that location.

Note that the purple “65” pin location revealed this common ancestor whose surname is spelled differently in our trees. This surname transitioned back and forth, so there I no “right” or “wrong” way to spell it. However, a different spelling may keep the person from being recognized as the same individual by computer software.

Now, let’s review Bonnie’s shared DNA match information.

Bonnie’s Shared DNA Matches

We know that each of the people in the first cluster match the tester, me, and all but 3 (yellow stars) of the people who match me in the first cluster also match Bonnie

However, don’t think for one minute that there are only 8 people who match me and Bonnie both. There are only 8 who match us both AND are included in the cluster. These are judged to be out “best” common matches.

Looking at my DNA match with Bonnie, I see that there are 162 total shared matches.

The balance, other than the 8 in the cluster, did not meet all of the match threshold ranges to be included in the cluster. In other words, shared matches not in the cluster were either less than 40 cM or more than 350 cM, or the shared piece of the matching segment was less than 15 cM. In other words, the matches in the cluster are the strongest shared matches, other than close relatives, but they certainly aren’t the only shared matches.

I match Bonnie on two segments, one on chromosome 13 and one on chromosome 16.

Just because someone matches me and Bonnie, both, doesn’t necessarily mean the match is on the same segment. For example, they could match me on chromosome 10 and Bonnie on chromosome 1, while Bonnie and I match each other on chromosomes 13 and 16.

However, there’s certainly a good chance that someone matches us both on the same segment(s).

Reviewing the cluster matches between me and Bonnie, we discover the following information regarding these two specific segments on chromosome 13 and 16, only.

Shared Match with Bonnie Triangulation Chromosome & Location
Sharon Yes Chr 16 only
Renee Yes Chr 16 only
Wilma Yes Chr 16 only
John Yes Chr 16 only
Celeste Yes Chr 16 only
Shirley No Neither
Carolyn Yes Chr 16 only
Ray No Neither

Six people match me and Bonnie both on chromosome 16, none match me and Bonnie both on chromosome 13, so that means that both Shirley and Ray match both of us on a completely different chromosome segment.

Now, of course, the question becomes if those 6 people match Bonnie and me on the same or at least an overlapping portion of chromosome 16.

Triangulation

Triangulation, which I wrote about here, occurs when the tester matches two or more people on the same reasonably sized segment of DNA, and they also match each other on that same segment. The “matching each other” part is important, because it verifies the match is from the same side, Mom or Dad, and from a common ancestor, not identical by chance (IBC).

I wrote about identical by chance here, but in essence, IBC means that a piece of your Mom’s DNA and a piece of your Dad’s DNA accidentally combined in you to look like a match with someone else, but it’s a false positive. You do technically “match” that other person, but it’s because of chance recombination, not because you share DNA from a common ancestor on one side of your family or the other.

The matching to other known family members on that segment is the clue to eliminating IBC matches from comparisons. Each of your valid matches will match one of your parents, or the other. If your match doesn’t also match one or the other parent, it’s not a valid match.

This is known as parental phasing and is why it’s extremely important to have both or one of your parents test, if possible.

If the tester’s parents have tested, each of your cluster matches will match to one parent or the other in addition to the people in the cluster.

Bonnie Has Triangulated Matches!

At MyHeritage, when you review shared matches, you can see if your match triangulates with you by the presence of a little purple triangulate icon.

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Looking at my shared match list with Bonnie, I see Wilma has a purple icon, indicating triangulation between Wilma, Bonnie and me. Woohooo!

Clicking on the purple triangulate icon shows me the common triangulated segment(s).

In this case, Bonnie, Wilma and I only triangulate on one segment, on chromosome 16. Do the other cluster members also triangulate with Bonnie, Wilma and me on this segment? The ones who have a triangulation icon should since I’ve already determined that they only match me on chromosome 16 in common with Bonnie. Let’s see.

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I added the other people in the match cluster to see who else triangulates on any portion of chromosome 16. Just type the names from the cluster into the DNA match name box below the profile cards in the chromosome browser to add each person to the view.

Only the triangulated portion for all people compared is bracketed. That’s so important to remember. In the example above, all people match me and each other on the bracketed portion of chromosome 16.

In this example, two of the people compared do NOT triangulate on this segment, so no bracket is drawn. This might lead you to think that the three people whose DNA matches the tester on the same segment don’t also match each other – but you can’t assume.

If you remove the two people not matching on the segment from the chromosome browser, the other three now show the triangulation bracket.

Triangulated segments provide evidence that a specific segment descends from a common ancestor. The challenge, of course, is to identify the ancestors who contributed that segment generationally through time.

I wrote about triangulation at MyHeritage in the article Triangulation in Action at MyHeritage.

Downloads

You can only compare a maximum of 7 people at a time in the chromosome browser, but you can download your entire match list in a spreadsheet and work from there. I do that often.

There are three different downloads that provide different information and serve a different purpose.

Chromosome Browser Match Download

Scroll down to the bottom of the chromosome browser page to download the matching segments (to you) of the people shown on the browser at that time.

You can download the segments for the current matches showing in the chromosome browser by clicking on advanced options on that page.

Click on “Download shared DNA info.”

This download will happen immediately to your system. I use this technique when chromosome painting matches identified to a particular ancestor at DNAPainter. I also note for each match when I’ve painted their matching segments so I don’t waste time doing it twice.

The second and third download options are found on your DNA Match page.

Export Full Match List and Shared DNA Segments

By moving to your main DNA match page, you can download:

  • Your DNA match list which downloads information about each of your matches
  • Your matching DNA segments for all matches

By clicking on the three dots, you will see the two download/export options. Those two files hold different information.

The “entire DNA matches list” provides information ABOUT your matches, such as:

  • Name
  • Age
  • Country
  • Contact link
  • DNA manager
  • Status (new)
  • Estimated relationship
  • Total cMs
  • Percent shared DNA
  • Number of shared segments
  • Largest segment
  • Link to review DNA match
  • Has tree (yes/no)
  • Number of people in tree
  • Tree manager
  • Contract tree link
  • Number of smart matches
  • Shared ancestral surnames
  • All ancestral surnames
  • Notes

This is important, and I use this file a lot because it provides all of the information in one place and I don’t have to click on each match to evaluate. Plus, I can search and sort to my heart’s content.

Option two, the entire “shared segment DNA info” match list will show all matches, including maternal, paternal and IBC. It’s up to you to figure out which are which, but we have lots of tools and hints.

Your shared segment spreadsheet provides information about the shared DNA, only.

Let’s start by looking at Bonnie again.

Bonnie and Chromosome 16 on the Spreadsheet

Here are my two segment matches with Bonnie in the spreadsheet.

The MyHeritage tools, combined, provide you with the ability to sort your matches meaningfully into genealogically relevant clusters and identify ancestors. I’m going to utilize that information with the downloaded spreadsheet segment information.

Let’s take a look at that matching segment with Bonnie on chromosome 16.

In the shared DNA segment spreadsheet, I filtered for chromosome 16, sorted in lowest to highest order (end location, then start) and looked for matches that fall between these two locations.

In reference to the match with Bonnie, look for any match between 79914629 and 87713399.

I am showing only a partial list below. The actual number of matches to be on this segment of chromosome 16 is about three times as large as this graphic.

After downloading the spreadsheet, I added a Triangulation Group column and a comments column, at right.

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I’ve colored the cluster members yellow who match on chromosome 16 to Bonnie AND me in the cluster.

People who match me on chromosome 16 and are NOT in the cluster fall into one of the following categories:

  • Also match to me and Bonnie, but outside of the cluster threshold. You can see that there are a lot of matches below 40 cM, which immediately eliminates them from the cluster.
  • Match me and Bonnie, but on an overlapping piece of DNA not large enough to be included in a cluster – in other words, the overlap of the three people is less than 15 cM..
  • Match to me, but not Bonnie which means that either they are a match from the other parent’s side, or identical by chance.

Discerning which category each match falls into requires looking at each match and evaluating individually.

You can look at each spreadsheet row, individually, below, if you wish, but what I’d like for you to do is to focus on the groups that I created as I analyzed each match on the segment of chromosome 16 where I match Bonnie.

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  • Green row is Bonnie, our baseline person whose match is why I’m analyzing this particular segment.
  • Bright yellow shows the 6 AutoCluster triangulated chromosome 16 cluster members.
  • Lighter yellow rows are also matches and triangulations on the same segment with me and Bonnie, but not included in the AutoCluster
  • Pink indicates matches on Mom’s side on this same chromosome segment. Mom is in the database, so this is easy to discern.
  • Grey is IBC (darker) or likely IBC (lighter) meaning they don’t match either parent’s side entirely.
  • Bright red is a breakthrough!

You’ll notice that the “best” matches, meaning the ones in the cluster, are clustered together on the spreadsheet too.

The second group of matches, below, begins to have more IBC and matches to Mom’s side. A third group, which I’m not including here, is almost entirely Mom’s side.

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When I finished analyzing the matches on this segment of chromosome 16 from the AutoCluster, I had:

  • Bonnie (green) + 6 Claxton matches (bright yellow) reflecting the first cluster triangulation with Bonnie and me
  • 93 total people that matched me on some portion of chromosome 16 that I match in common with Bonnie. However, on this spreadsheet, matches to me on this segment include some matches who will not match Bonnie.
  • People not matching me and Bonnie both on this segment will include both matches on Mom’s side (pink), and IBC (grey).
  • A breakthrough (bright red) identifying this segment as Claxton, as opposed to Sarah Cook’s, James Claxton’s wife, which means that I can focus on other people with trees with common ancestors who match on that segment on Dad’s side. Someplace in those trees is the information that will someday identify James Claxton’s parents/ancestors.
  • Identified 28 (light yellow) paternal matches through this segment assigned to Claxton that match me and Bonnie, both.
  • Identified 30 (pink) Mom segments, some of which are Acadian and some of which are German. On Mom’s side, two different portions of chromosome 16 recombined from two different ancestors and I can tell where that dividing line occurs by using visual phasing and triangulation at DNAPainter.
  • Identified 26 (grey) IBC segments which are false positive (or likely false positive) matches and should be disregarded.
  • Made notes on each of those matches at MyHeritage.
  • Painted each valid segment at DNAPainter.

About That BreakThrough…

Why is this breakthrough important, and what does it tell me?

Bonnie is descended from the same Claxton line as I am, meaning she is a proven descendant of James Lee Claxton born about 1775 and his wife, Sarah Cook through their son, Fairwick/Fairwix Claxton. We don’t know where James Claxton was born, but likely in either VA or NC. He first appeared on the tax list in Russell County, VA, with no other Claxton males, not long before he married Sarah in 1799.

Bonnie and I match Jim on that same segment.

Jim’s ancestor was Solomon Claxton, born in 1801 in NC. In other words, Jim does NOT share James Claxton as a common ancestor. This means that Jim and Bonnie and I share DNA from a common Claxton ancestor. That segment of chromosome 16 cannot be from the Cook side, because Jim does not descend from the James Claxton/Sarah Cook line.

Therefore, other people who triangulate on that segment, who don’t show trees with Claxton ancestors, and have matching trees to each other will one day hold the key to our common ancestors who contributed that segment to all of us on chromosome 16.

That means I need to take the time to evaluate every one of their trees looking for their common ancestors with each other. It’s likely that common ancestor could be mine as well, or lead to mine.

Just One!!!

Remember, all of the discoveries above were made from analyzing just one chromosome segment match from the Bonnie row in the first AutoCluster. Just one!

Autoclusters intentionally only utilize your “best” non-close family member matches. This allows you to see the genetic relationships between multiple people, even without trees.

You then use the trees, TOFR, surnames, locations, Smart Matches, shared matches, triangulation, and previous research to identify the ancestral connection.

Just scanning this AutoCluster report, I can immediately discern that people share matches between groups of clusters. For example, clusters 1, 2, and 4 share members – for starters. That tells me that these clusters are related to each other. In fact, that’s exactly correct as shown after analysis when I was able to assign each cluster to either an ancestor or ancestral couple.

I discovered a HUGE amount of information researching just one common segment with one match, including a breakthrough which may, one day, if not today, lead to the identification of James Claxton’s parents.

Just think how much more there is left to discover! I need to review the match to Bonnie on chromosome 13 and the other 99 people in my AutoCluster, utilizing the same tools and techniques.

I can hardly wait to get started!

Clusters are Genetic Super-Powers

Clusters are your super-power matches. Take full advantage of them.

  • Every cluster tells a story.
  • If you can identify the common ancestors with one or two people, and it’s the same line, you’ve probably identified the genetic “cluster.”
  • Every match tells a story.
  • You may triangulate on multiple segments with different people.
  • Every individual segment tells a story
  • Each segment stands alone, meaning one segment can descend from the mother of the couple, and another segment from the father. Don’t assume that each shared segment descends from the same ancestor.
  • Don’t assume that if you match one person on two segments, that they both necessarily descend from the same line or couple. It’s possible that you are related on another, known or unknown, line.
  • Every segment match has an individual genealogical history that can lead to different ancestors, meaning that the genetic line is the same, but the ancestors may be different. You may match one person who descends from the son of another match, for example.
  • Each triangulated segment descended from common ancestors who contributed that segment to all triangulation group members.
  • The history of brick walls is held in unidentified matches to segments.

An example is worth 1000 words.

Walking Back In Time

Based on multiple triangulated matches to various people, the triangulated segment on chromosome 16 belongs to the following ancestors:

Generation Ancestor Via Match to…
1 Dad Assigned to Dad’s side via triangulated matches to known relatives
2 Ollie Bolton Culley, Stacey
3 Margaret Clarkson Fred, John
4 Samuel Claxton Wilma
5 Fairwick Claxton Joy, Eugene, Billy, I.B., Bonnie
6 James Claxton, Sarah Cook Brent, Delilah
7 Unknown Claxton parents Jim (NC), Kelsey (TN)

As you can see, based on the genealogy of my matches, I’ve walked the segment on chromosome 16 back in time 7 generations.

How do I get to generation 8?

Clusters are Genetic Super-Powers

Now I need to search the trees of matches on this same segment, but without identified common ancestors to me, looking for common lineages in their trees with each other.

This Claxton segment descended from some unknown ancestor(s) upstream of James Claxton. The key to the identity of those ancestors is held in their DNA segments and matches.

What I’m looking for are common ancestors of those chromosome 16 matches to each other. For example, if James Claxton’s father was named John Claxton and his mother was Jane Doe, finding several people with trees connecting to the Doe family would be especially relevant. Those are the more deeply hidden clues.

I need to do the exact same thing, following the same process, with each segment of every cluster match!

The solution to brick walls is held in unidentified matches to triangulated segments which point the way – like invisible “this way” arrows through that door from our ancestors.

AutoClusters are the genetic superpower!

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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

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Join Me For “How to Use AutoClusters to Analyze Your DNA Matches,” Live and Free

Please accept this invitation to join me this Wednesday, October 21, at 2 PM EST, for the MyHeritage Facebook LIVE event, “How to Use AutoClusters to Analyze Your DNA Matches,” presented by yours truly! Please note that if you can’t join us for the live presentation, it will be available to view later. I’ll post a link when it becomes available – after the live session.

The live webinar is free, courtesy of MyHeritage, and me.

You can read about this event and other free October seminars in the MyHeritage blog article, here.

To view the session, simply click on the MyHeritage Facebook page, at this link, near that time and the session will appear as a posting. I can’t give you the link in advance because until the live session is occurring, there isn’t a link to post.

We will be covering how to use the AutoCluster feature that’s included for all MyHeritage DNA users, incorporating cluster information with other MyHeritage DNA tools such as Theories of Family Relativity, Smart Matches, Ancestral Surnames, Shared Matches, Locations and Triangulation to solve genealogical puzzles.

I even made a discovery when creating this workshop and I’ll share how that happened and why it’s important.

You have surprises waiting for you too. AutoCluster opens doors and breaks down brick walls.

It’s Not Too Late!

If you haven’t DNA tested at MyHeritage, you can purchase a test, here.

However, if you’ve already tested elsewhere, it’s much quicker and less expensive to upload your DNA file for free, here, and pay the $29 unlock fee to access the advanced tools, including AutoCluster. Step-by-step transfer instructions for all vendors are found, here.

Instead of paying the $29 unlock fee, you can subscribe to the MyHeritage genealogy research package and that will gain you access to the advanced DNA tools as well. You can sign up for a trial subscription for free, here.

See you on Wednesday!!!

_____________________________________________________________

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

Longobards Ancient DNA from Pannonia and Italy – What Does Their DNA Tell Us? Are You Related?

The Longobards, Lombards, also known as the Long-beards – who were they? Where did they come from? And when?

Perhaps more important – are you related to these ancient people?

In the paper, Understanding 6th-century barbarian social organizatoin and migration through paleogenomics, by Amorim et al, the authors tell us in the abstract:

Despite centuries of research, much about the barbarian migrations that took place between the fourth and sixth centuries in Europe remains hotly debated. To better understand this key era that marks the dawn of modern European societies, we obtained ancient genomic DNA from 63 samples from two cemeteries (from Hungary and Northern Italy) that have been previously associated with the Longobards, a barbarian people that ruled large parts of Italy for over 200 years after invading from Pannonia in 568 CE. Our dense cemetery-based sampling revealed that each cemetery was primarily organized around one large pedigree, suggesting that biological relationships played an important role in these early medieval societies. Moreover, we identified genetic structure in each cemetery involving at least two groups with different ancestry that were very distinct in terms of their funerary customs. Finally, our data are consistent with the proposed long-distance migration from Pannonia to Northern Italy.

Both the Germans and French have descriptions of this time of upheaval in their history. Völkerwanderung in German and Les invasions barbares in French refer to the various waves of invasions by Goths, Franks, Anglo-Saxons, Vandals, and Huns. All of these groups left a genetic imprint, a story told without admixture by their Y and mitochondrial DNA.

click to enlarge

The authors provide this map of Pannonia, the Longobards kingdom, and the two cemeteries with burial locations.

One of their findings is that the burials are organized around biological kinship. Perhaps they weren’t so terribly different from us today.

Much as genealogists do, the authors created a pedigree chart – the only difference being that their chart is genetically constructed and lacks names, other than sample ID.

One man is buried with a horse, and one of his relatives, a female, is not buried in a family unit but in a half-ring of female graves.

The data suggests that the cemetery in Pannonia, Szolad, shown in burgundy on the map, may have been a “single-generation” cemetery, in use for only a limited time as the migration continued westward. Collegno, in contrast, seems to have been used for multiple generations, with the burials radiating outward over time from the progenitor individual.

Because the entire cemetery was analyzed, it’s possible to identify those individuals with northern or northeastern European ancestry, east of the Rhine and north of the Danube, and to differentiate from southern European ancestry in the Lombard cemetery – in addition to reassembling their family pedigrees. The story is told, not just by one individual’s DNA, but how the group is related to each other, and their individual and group origins.

For anyone with roots in Germany, Hungary, or the eastern portion of Europe, you know that this region has been embroiled in upheaval and warfare seemingly as long as there have been people to fight over who lived in and controlled these lands.

Are You Related?

Goran Rundfeldt’s R&D group at Family Tree DNA reanalyzed the Y DNA samples from this paper and has been kind enough to provide a summary of the results. Michael Sager has utilized them to branch the Y DNA tree – in a dozen places.

Mitochondrial DNA haplogroups have been included where available from the authors, but have not been reanalyzed.

Note the comments added by FTDNA during analysis.

Many new branches were formed. I included step-by-step instructions, here, so you can see if your Y DNA results match either the new branch or any of these samples upstream.

If you’re a male and you haven’t yet tested your Y DNA or you would like to upgrade to the Big Y-700 to obtain your most detailed haplogroup, you can do either by clicking here. My husband’s family is from Hungary and I just upgraded his Y DNA test to the Big Y-700. I want to know where his ancestors came from.

And yes, this first sample really is rare haplogroup T. Each sample is linked to the Family Tree DNA public tree. We find haplogroups G and E as well as the more common R and I. Some ancient samples match contemporary testers from France (2), the UK, England, Morocco, Denmark (5), and Italy. Fascinating!

Sample: CL23
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: T-BY45363
mtDNA: H

Sample: CL30
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-P312
mtDNA: I1b

Sample: CL31
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: G-FGC693
FTDNA Comment: Authors warn of possible contamination. Y chromosome looks good – and there is support for splitting this branch. However, because of the contamination warning – we will not act on this split until more data is available.
mtDNA: H18

Sample: CL38
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: E-BY3880
mtDNA: X2

Sample: CL49
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-CTS6889

Sample: CL53
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-FGC24138
mtDNA: H11a

Sample: CL57
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-BY48364
mtDNA: H24a

Sample: CL63
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: I-FT104588
mtDNA: H

Sample: CL84
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-U198
mtDNA: H1t

Sample: CL92
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-S22519
mtDNA: H

Sample: CL93
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-S22519
mtDNA: J2b1a

Sample: CL94
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-DF99
mtDNA: K1c1

Sample: CL97
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-L23

Sample: CL110
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-L754

Sample: CL121
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-BY70163
FTDNA Comment: Shares 2 SNPs with a man from France. Forms a new branch down of R-BY70163 (Z2103). New branch = R-BY197053
mtDNA: T2b

Sample: CL145
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-S22519
mtDNA: T2b

Sample: CL146
Location: Collegno, Piedmont, Italy
Age: Longobard 6th Century
Y-DNA: R-A8472
mtDNA: T2b3

Sample: SZ1
Location: Szólád, Somogy County, Hungary
Study Information: The skeletal remains from an individual dating to the Bronze Age 10 m north of the cemetery.
Age: Bronze Age
Y-DNA: R-Y20746
mtDNA: J1b

Sample: SZ2
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: R-Z338
FTDNA Comment: Shares 5 SNPs with a man from the UK. Forms a new branch down of R-Z338 (U106). New branch = R-BY176786
mtDNA: T1a1

Sample: SZ3
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: I-BY3605
mtDNA: H18

Sample: SZ4
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: R-ZP200
FTDNA Comment: Splits R-ZP200 (U106). Derived (positive) for 2 SNPs and ancestral (negative) for 19 SNPs. New path = R-Y98441>R-ZP200
mtDNA: H1c9

Sample: SZ5
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: R-BY3194
FTDNA Comment: Splits R-BY3194 (DF27). Derived for 19 SNPs, ancestral for 9 SNPs. New path = R-BY3195>R-BY3194
mtDNA: J2b1

Sample: SZ6
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: I-P214

Sample: SZ7
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: I-S8104
FTDNA Comment: SZ13, SZ7 and SZ12 share 2 SNPs with a man from Denmark, forming a branch down of I-S8104 (M223). New branch = I-FT45324. Note that SZ22 and SZ24 (and even SZ14) fall on the same path to I-S8104 but lack coverage for intermediate branches.
mtDNA: T2e

Sample: SZ11
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: R-FGC13492
FTDNA Comment: Shares 1 SNP with a man from Italy. Forms a new branch down of R-FGC13492 (U106). New branch = R-BY138397
mtDNA: K2a3a

Sample: SZ12
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: I-S8104
FTDNA Comment: SZ13, SZ7 and SZ12 share 2 SNPs with a man from Denmark, forming a branch down of I-S8104 (M223). New branch = I-FT45324. Note that SZ22 and SZ24 (and even SZ14) fall on the same path to I-S8104 but lack coverage for intermediate branches.
mtDNA: W6

Sample: SZ13
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century 422-541 cal CE
Y-DNA: I-S8104
FTDNA Comment: SZ13, SZ7 and SZ12 share 2 SNPs with a man from Denmark, forming a branch down of I-S8104 (M223). New branch = I-FT45324. Note that SZ22 and SZ24 (and even SZ14) fall on the same path to I-S8104 but lack coverage for intermediate branches.
mtDNA: N1b1b1

Sample: SZ14
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: I-CTS616
FTDNA Comment: SZ13, SZ7 and SZ12 share 2 SNPs with a man from Denmark, forming a branch down of I-S8104 (M223). New branch = I-FT45324. Note that SZ22 and SZ24 (and even SZ14) fall on the same path to I-S8104 but lack coverage for intermediate branches.
mtDNA: I3

Sample: SZ15
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: R-YP986
mtDNA: H1c1

Sample: SZ16
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: R-U106
mtDNA: U4b1b

Sample: SZ18
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: E-BY6865
FTDNA Comment: Shares 1 SNP with a man from Morocco. Forms a new branch down of E-BY6865. New branch = E-FT198679
mtDNA: H13a1a2

Sample: SZ22
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: I-Y6876
FTDNA Comment: SZ13, SZ7 and SZ12 share 2 SNPs with a man from Denmark, forming a branch down of I-S8104 (M223). New branch = I-FT45324. Note that SZ22 and SZ24 (and even SZ14) fall on the same path to I-S8104 but lack coverage for intermediate branches.
mtDNA: N1b1b1

Sample: SZ23
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: R-S10271
mtDNA: H13a1a2

Sample: SZ24
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: I-ZS3
FTDNA Comment: SZ13, SZ7 and SZ12 share 2 SNPs with a man from Denmark, forming a branch down of I-S8104 (M223). New branch = I-FT45324. Note that SZ22 and SZ24 (and even SZ14) fall on the same path to I-S8104 but lack coverage for intermediate branches.
mtDNA: U4b

Sample: SZ27B
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century 412-538 cal CE
Y-DNA: R-FGC4166
FTDNA Comment: Shares 1 SNP with a man from France. Forms a new branch down of R-FGC4166 (U152). New branch = R-FT190624
mtDNA: N1a1a1a1

Sample: SZ36
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: T-Y15712
mtDNA: U4c2a

Sample: SZ37
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century 430-577 cal CE
Y-DNA: R-P312
mtDNA: H66a

Sample: SZ42
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century
Y-DNA: R-P312
mtDNA: K2a6

Sample: SZ43
Location: Szólád, Somogy County, Hungary
Age: Longobard 6th Century 435-604 cal CE
Y-DNA: I-BY138
mtDNA: H1e

Sample: SZ45
Location: Szólád, Somogy County, Hungary
Study Information: ADMIXTURE analysis showed SZ45 to possess a unique ancestry profile.
Age: Longobard 6th Century
Y-DNA: I-FGC21819
FTDNA Comment: Shares 2 SNPs with a man from England forms a new branch down of FGC21819. New branch = I-FGC21810
mtDNA: J1c

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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 Y DNA Webinar at Legacy Family Tree Webinars

I just finished recording a new, updated Y DNA webinar, “Wringing Every Drop out of Y DNA” for Legacy Family Tree Webinars and it’s available for viewing now.

This webinar is packed full of information about Y DNA testing. We discuss the difference between STR markers, SNPs and the Big Y test. Of course, the goal is to use these tests in the most advantageous way for genealogy, so I walk you through each step. There’s so much available that sometimes people miss critical pieces!

FamilyTreeDNA provides a wide variety of tools for each tester in addition to advanced matching which combines Y DNA along with the Family Finder autosomal test. Seeing who you match on both tests can help identify your most recent common ancestor! You can order or upgrade to either or both tests, here.

During this 90 minute webinar, I covered several topics.

There’s also a syllabus that includes additional resources.

At the end, I summarized all the information and show you what I’ve done with my own tree, illustrating how useful this type of testing can be, even for women.

No, women can’t test directly, but we can certainly recruit appropriate men for each line or utilize projects to see if our lines have already tested. I provide tips and hints about how to successfully accomplish that too.

Free for a Limited Time

Who doesn’t love FREE???

The “Squeezing Every Drop out of Y DNA” webinar is free to watch right now, and will remain free through Wednesday, October 14, 2020. On the main Legacy Family Tree Webinar page, here, just scroll down to the “Webinar Library – New” area to see everything that’s new and free.

If you’re a Legacy Farmily Tree Webinar member, all webinars are included with your membership, of course. I love the great selection of topics, with more webinars being added by people you know every week. This is the perfect time to sign up, with fall having arrived in all its golden glory and people spending more time at home right now.

More than 4000 viewers have enjoyed this webinar since yesterday, and I think you will too. Let’s hope lots of people order Y DNA tests so everyone has more matches! You just never know who’s going to be the right match to break down those brick walls or extend your line back a few generations or across the pond, perhaps.

You can view this webinar after October 14th as part of a $49.95 annual membership. If you’d like to join, click here and use the discount code ydna10 through October 13th.

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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 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

click to enlarge

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.

click to enlarge

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!!!

_____________________________________________________________

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

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.

click to enlarge

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

click to enlarge

  • 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.

click to enlarge

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.

click to enlarge

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

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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

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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

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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

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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

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  • 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.

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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

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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

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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

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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

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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

click to enlarge

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