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

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.

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Genealogy Products and Services

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Shared cM Project 2020 Analysis, Comparison & Handy Reference Charts

Recently, Blaine Bettinger published V4 of the Shared cM Project, and along with that, Jonny Perl at DNAPainter updated the associated interactive tool as well, including histograms. I wrote about that, here.

The goal of the shared cM project was and remains to document how much DNA can be expected to be shared by various individuals at specific relationship levels. This information allows matches to at least minimally “position” themselves in a general location their trees or conversely, to eliminate specific potential relationships.

Shared cM Project match data is gathered by testers submitting their match information through the submission portal, here.

When the Shared cM Project V3 was released in September 2017, I combined information from various sources and provided an analysis of that data, including the changes from the V2 release in 2016.

I’ve done the same thing this year, adding the new data to the previous release’s table.

Compiled Comparison Table

I initially compiled this table for myself, then decided to update it and share with my readers. This chart allows me to view various perspectives on shared data and relationships and in essence has all the data I might need, including multiple versions, in one place. Feel free to copy and save the table.

In the comparison table below, the relationship rows with data from various sources is shown as follows:

  • White – Shared cM Project 2016
  • Peach – Shared cM Project 2017
  • Purple – Shared cM Project 2020
  • Green – DNA Detectives chart

I don’t know if DNA Detectives still uses the “green chart” or if they have moved to the interactive DNAPainter tool. I’ve retained the numbers for historical reference regardless.

Additionally, in some places, you’ll see references to the “degree of relationship,” as in “third degree relatives always match each other.” I’ve included a “Degree of Relationship” column to the far right, but I don’t come across those “relationship degree” references often anymore either. However, it’s here for reference if you need it.

23andMe still gives relationships in percentages, so I’ve included the expected shared percent of DNA for each relationship and the actual shared range from the DNA Detectives Green Chart.

One column shows the expected shared cM amount, assuming that 50% of the DNA from each ancestor is passed on in each generation. Clearly, we know that inheritance doesn’t happen that cleanly because recombination is a random event and children do NOT inherit exactly half of each ancestor’s DNA carried by their parents, but the average should be someplace close to this number.

shared cm table 2020

click to open separately, then use your magnifier to enlarge

The first thing I noticed about V4 is that there is a LOT more data which means that the results are likely more accurate. V4 increased by 32K data points, or 147%. Bravo to everyone who participated, to Blaine for the analysis and to Jonny for automating the results at DNAPainter.

Methods

Blaine provided his white paper, here, which includes “everything you need to know” about the project, and I strongly encourage you to read it. Not only does this document explain the process and methods, it’s educational in its own right.

On the first page, Blaine discusses issues. Any time you are crowd sourcing information, you’re going to encounter challenges and errors. Blaine did remove any entries that were clearly problematic, plus an additional 1% of all entries for each category – .5% from each end meaning the largest and smallest entries. This was done in an attempt to remove the results most likely to be erroneous.

Known issues include:

  • Data entry errors – I refer to these as “clerical mutations,” but they happen and there is no way, unless the error is egregious, to know what is a typo and what is real. Obviously, a parent sharing only a 10 cM segment with a child is not possible, but other data entry errors are well within the realm of possible.
  • Incorrect relationships – Misreported or misunderstood relationships will skew the numbers. Relationships may be believed to be one type, but are actually something else. For example, a half vs full sibling, or a half vs full aunt or uncle.
  • Misunderstood Relationships – People sometimes become confused as to the difference between “half” and “removed” from time to time. I wrote a helpful article titled Quick Tip – Calculating Cousin Relationships Easily.
  • Endogamy – Endogamy occurs when a population intermarries within itself, meaning that the same ancestral DNA is present in many members of the community. This genetic result is that you may share more DNA with those cousins than you would otherwise share with cousins at the same distance without endogamy.
  • Pedigree Collapse – Pedigree collapse occurs when you find the same ancestors multiple times in your tree. The closer to current those ancestors appear, the more DNA you will potentially carry from those repeat ancestors. The difference between endogamy and pedigree collapse is that endogamy is a community event and pedigree collapse has only to do with your own tree. You might just have both, too.
  • Company Reporting Differences – Different companies report DNA in different ways in addition to having different matching thresholds. For example, Family Tree DNA includes in your match total all DNA to 1 cM that you share with a match over the matching threshold. Conversely, Ancestry has a lower matching threshold, but often strips out some matching DNA using Timber. 23andMe counts fully identical segments twice and reports the X chromosome in their totals. MyHeritage does not report the X chromosome. There is no “right” or “wrong,” or standardization, simply different approaches. Hopefully, the variances will be removed or smoothed in the averages.
  • Distant Cousin Relationships – While this isn’t really an issue, per se, it’s important to understand what is being reported beyond 2nd cousin relationships in that the only relationships used to calculate these averages is the DNA from people who DO share DNA with their more distant cousins. In other words, if you do NOT match your 3rd cousin, then your “0” shared DNA is not included in the average. Only those who do match have their matching amounts included. This means that the average is only the average of people who match, not the average of all 3rd cousins.

Challenges aside, the Shared cM Project provides genealogists with a wonderful opportunity to use the combined data of tens of thousands of relationships to estimate and better understand the relationship range of our matches.

The Shared cM Project in combination with DNAPainter provides us with a wonderful tool.

Histograms

When analyzing the data, one of the first things I noticed was a very unusual entry for parent/child relationships.

We all know that children each inherit exactly half of their parent’s DNA. We expect to find an amount in the ballpark of 3400, give or take a bit for normal variances like read errors or reporting differences.

Shared cM parent child.png

click to enlarge

I did not expect to see a minimum shared cM amount for a child/parent relationship at 2376, fully 1024 cM below expected value of 3400 cM. Put bluntly, that’s simply not possible. You cannot live without one third of one of your parent’s DNA. If this data is actually accurate from someone’s account, please contact me because I want to actually see this phenomenon.

I reached out to Blaine, knowing this result is not actually possible, wondering how this would ever get through the quality control cycle at any vendor.

After some discussion, here’s Blaine’s reply:

If you look at the histogram, you’ll see that those are most likely outliers. One of my lessons for the ScP (Shared cM Project) lately is that people shouldn’t be using the data without the histograms.

People get frustrated with this, but I can’t edit data without a basis even if I think it doesn’t make sense. I have to let the data itself decide what data to remove. So I removed 1% from each relationship, the lowest 0.5% and the highest 0.5%. I could have removed more, but based on the histograms, [removing] more appeared to be removing too much valid data. As people submit more parent/child relationships these outliers/incorrect submissions will be removed. But thankfully using the histograms makes it clear.

Indeed, if you look on page 23 on Blaine’s white paper, you’ll see the following histogram of parent/child relationships submitted.

shared cm histogram.png

click to enlarge

Keep in mind that Blaine already removed any obvious errors, plus 1% of the total from either end of the spectrum. In this case, he utilized 2412 submissions, so he would have removed about 24 entries that were even further out on the data spectrum.

On the chart above, we can see that a total of about 14 are still really questionable. It’s not until we get to 3300 that these entries seem feasible. My speculation is that these people meant to type 3400 instead of 2400, and so forth.

shared cm parent grid.png

click to enlarge

The great news is that Jonny Perl at DNAPainter included the histograms so you can judge for yourself if you are in the weeds on the outlier scale by clicking on the relationship.

shared cm parent submissions.png

click to enlarge

Other relationships, like this niece/nephew relationship fit the expected bell shaped curve very nicely.

shared cm niece.png

Of course, this means that if you match your niece or nephew at 900 cM instead of the range shown above, that person is probably not your full niece or nephew – a revelation that may be difficult because of the implications for you, your parent and sibling. This would suggest that your sibling is a half sibling, not a full sibling.

Entering specific amounts of shared DNA and outputting probabilities of specific relationships is where the power of DNAPainter enters the picture. Let’s enter 900 cM and see what happens.

shared cm half niece.png

That 900 cM match is likely your half niece or nephew. Of course, this example illustrates perfectly why some relationships are entered incorrectly – especially if you don’t know that your niece or nephew is a half niece or nephew – because your sibling is a half-sibling instead of a full sibling. Some people, even after receiving results don’t realize there is a discrepancy, either because their data is on the boundary, with various relationships being possible, or because they don’t understand or internalize the genetic message.

shared cm full siblings.png

click to enlarge

This phenomenon probably explains the low minimum value for full siblings, because many of those full siblings aren’t. Let’s enter 1613 and see what DNAPainter says.

shared cm half sibling.png

You’ll notice that DNAPainter shows the 1613 cM relationship as a half-sibling.

shared cm sibling.png

And the histogram indeed shows that 1613 would be the outlier. Being larger that 1600, it would appear in the 1700 category.

shared cm half vs full.png

click to enlarge

Accurately discerning close relationships is often incredibly important to testers. In the histogram chart above, you can see that the blue and orange histograms plotted on the same chart show that there is only a very small amount of overlap between the two histograms. This suggests that some people, those in the overlap range, who believe they are full siblings are in reality half-siblings, and possibly, a few in the reverse situation as well.

What Else is Noteworthy?

First, some relationships cannot be differentiated or sorted out by using the cM data or histogram charts alone.

shared cm half vs aunt.png

click to enlarge

For example, you cannot tell the difference between half-siblings and an aunt/uncle relationship. In order to make that determination, you would need to either test or compare to additional people or use other clues such as genealogical research or geographic proximity.

Second, the ranges of many relationships are wider than they were before. Often, we see the lows being lower and the highs being higher as a result of more data.

shared cm low high.png

click to enlarge

For example, take a look at grandparents. The expected relationship is 1700 cM, the average is 1754 which is very close to the previous average numbers of 1765 and 1766. However, the minimum is now 984 and the new maximum is 2462.

Why might this be? Are ranges actually wider?

Blaine removed 1% each time, which means that in V3, 6 results would have been removed, 3 from each end, while 11 would be removed in V4. More data means that we are likely to see more outliers as entries increase, with the relationship ranges are increasingly likely to overlap on the minimum and maximum ends.

Third, it’s worth noting that several relationships share an expected amount of DNA that is equal, 12.5% which equals 850 cM, in this example.

shared cm 4 relationships.png

click to enlarge

These four relationships appear to be exactly the same, genetically. The only way to tell which one of these relationships is accurate for a given match pair, aside from age (sometimes) and opportunity, is to look at another known relationship. For example, how closely might the tester be related to a parent, sibling, aunt, uncle or first cousin, or one of their other matches. Occasionally, an X chromosome match will be enlightening as well, given the unique inheritance path of the X chromosome.

Additional known relationships help narrow unknown relationships, as might Y DNA or mitochondrial DNA testing, if appropriate. You can read about who can test for the various kinds of tests, here.

Fourth, it’s been believed for several years that all 5th degree relatives, and above, match, and the V4 data confirms that.

shared cm 5th degree.png

click to enlarge

There are no zeroes in the column for minimum DNA shared, 4th column from right.

5th degree relatives include:

  • 2nd cousins
  • 1st cousins twice removed
  • Half first cousins once removed
  • Half great-aunt/uncle

Fifth, some of your more distant cousins won’t match you, beginning with 6th degree relationships.

shared cm disagree.png

click to enlarge

At the 6th degree level, the following relationships may share no DNA above the vendor matching threshold:

  • First cousins three times removed
  • Half first cousins twice removed
  • Half second cousins
  • Second cousins once removed

You’ll notice that the various reporting models and versions don’t always agree, with earlier versions of the Shared cM Project showing zeroes in the minimum amount of DNA shared.

Sixth, at the 7th degree level, some number of people in every relationship class don’t share DNA, as indicated by the zeros in the Shared cM Minimum column.

shared cm 7th degree.png

click to enlarge

The more generations back in time that you move, the fewer cousins can be expected to match.

shared cm isogg cousin match.png

This chart from the ISOGG Wiki Cousin statistics page shows the probability of matching a cousin at a specific level based on information provided by testing companies.

Quick Reference Chart Summary

In summary, V4 of the Shared cM Project confirms that all 2nd cousins can expect to match, but beyond that in your trees, cousins may or may not match. I suspect, without evidence, that the further back in time that people are related, the less likely that the proper “cousinship level” is reported. For example, it would be easier to confuse 7th and 8th cousins as compared to 1st and 2nd cousins. Some people also confuse 8th cousins with 8 generations back in your tree. It’s not equivalent.

shared cm eighth cousin.png

click to enlarge

It’s interesting to note that Degree 17 relatives, 8th cousins, 9 generations removed from each other (counting your parents as generation 1), still match in some cases. Note that some companies and people count you as generation 1, while others count your parents as generation 1.

The estimates of autosomal matching reaching 5 or 6 generations back in time, meaning descendants of common 4 times great-grandparents will sometimes match, is accurate as far as it goes, although 5-6 generations is certainly not a line in the sand.

It would be more accurate to state that:

  • 2nd cousins, people descended from common great-grandparents, 3 generations back in time will always match
  • 4th cousins, people descended from common 3 times great grandparents, 5 generations back in time, will match about half of the time
  • 8th cousins, people descended from 7 times great grandparents, 9 generations back in time still match a small percentage of the time
  • Cousins from more distant ancestors can possibly match, but it’s unlikely and may result from a more recent unknown ancestor

I created this summary chart, combining information from the ISOGG chart and the Shared cM Project as a handy quick reference. Enjoy!

shared cm quick reference.png

click to enlarge

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Disclosure

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

Thank you so much.

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Genealogy Products and Services

Genealogy Research

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DNAPainter Instructions and Resources

DNAPainter garden

DNAPainter is one of my favorite tools because DNAPainter, just as its name implies, facilitates users painting their matches’ segments on their various chromosomes. It’s genetic art and your ancestors provide the paint!

People use DNAPainter in different ways for various purposes. I utilize DNAPainter to paint matches with whom I’ve identified a common ancestor and therefore know the historical “identity” of the ancestors who contributed that segment.

Those colors in the graphic above are segments identified to different ancestors through DNA matching.

DNAPainter includes:

  • The ability to paint or map your chromosomes with your matching segments as well as your ethnicity segments
  • The ability to upload or create trees and mark individuals you’ve confirmed as your genetic ancestors
  • A number of tools including the Shared cM Tool to show ranges of relationships based on your match level and WATO (what are the odds) tool to statistically predict or estimate various positions in a family based on relationships to other known family members

A Repository

I’ve created this article as a quick-reference instructional repository for the articles I’ve written about DNAPainter. As I write more articles, I’ll add them here as well.

  • The Chromosome Sudoku article introduced DNAPainter and how to use the tool. This is a step-by-step guide for beginners.

DNA Painter – Chromosome Sudoku for Genetic Genealogy Addicts

  • Where do you find those matches to paint? At the vendors such as Family Tree DNA, MyHeritage, 23andMe and GedMatch, of course. The Mining Vendor Matches article explains how.

DNAPainter – Mining Vendor Matches to Paint Your Chromosomes

  • Touring the Chromosome Garden explains how to interpret the results of DNAPainter, and how automatic triangulation just “happens” as you paint. I also discuss ethnicity painting and how to handle questionable ancestors.

DNA Painter – Touring the Chromosome Garden

  • You can prove or disprove a half-sibling relationship using DNAPainter – for you and also for other people in your tree.

Proving or Disproving a Half Sibling Relationship Using DNAPainter

  • Not long after Dana Leeds introduced The Leeds Method of clustering matches into 4 groups representing your 4 grandparents, I adapted her method to DNAPainter.

DNAPainter: Painting the Leeds Method Matches

  • Ethnicity painting is a wonderful tool to help identify Native American or minority ancestry segments by utilizing your estimated ethnicity segments. Minority in this context means minority to you.

Native American and Minority Ancestors Identified Using DNAPainter Plus Ethnicity Segments

  • Creating a tree or uploading a GEDCOM file provides you with Ancestral Trees where you can indicate which people in your tree are genetically confirmed as your ancestors.

DNAPainter: Ancestral Trees

  • Of course, the key to DNA painting is to have as many matches and segments as possible identified to specific ancestors. In order to do that, you need to have your DNA working for you at as many vendors as possible that provide you with matching and a chromosome browser. Ancestry does not have a browser or provide specific paintable segment information, but the other major vendors do, and you can transfer Ancestry results elsewhere.

DNAPainter: Painting “Bucketed” Family Tree DNA Maternal and Paternal Family Finder Matches in One Fell Swoop

  • Family Tree DNA offers the wonderful feature of assigning your matches to either a maternal or paternal bucket if you connect 4th cousins or closer on your tree. Until now, there was no way to paint that information at DNAPainter en masse, only manually one at a time. DNAPainter’s new tool facilitates a mass painting of phased, parentally bucketed matches to the appropriate chromosome – meaning that triangulation groups are automatically formed!

Triangulation in Action at DNAPainter

  • DNAPainter provides the ability to triangulate “automatically” when you paint your segments as long as you know which side, maternal or paternal, the match originates. Looking at the common ancestors of your matches on a specific segments tracks that segment back in time to its origins. Painting matches from all vendors who provide segment information facilitates once single repository for walking your DNA information back in time.

DNA Transfers

Some vendors don’t require you to test at their company and allow transfers into their systems from other vendors. Those vendors do charge a small fee to unlock their advanced features, but not as much as testing there.

Ancestry and 23andMe DO NOT allow transfers of DNA from other vendors INTO their systems, but they do allow you to download your raw DNA file to transfer TO other vendors.

Family Tree DNA, MyHeritage and GedMatch all 3 accept files uploaded FROM other vendors. Family Tree DNA and MyHeritage also allow you to download your raw data file to transfer TO other vendors.

These articles provide step-by-step instructions how to download your results from the various vendors and how to upload to that vendor, when possible.

Here are some suggestions about DNA testing and a transfer strategy:

Paint and have fun!!!

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Disclosure

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

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Services

Genealogy Research

First Steps When Your DNA Results are Ready – Sticking Your Toe in the Genealogy Water

First steps helix

Recently someone asked me what the first steps would be for a person who wasn’t terribly familiar with genealogy and had just received their DNA test results.

I wrote an article called DNA Results – First Glances at Ethnicity and Matching which was meant to show new folks what the various vendor interfaces look like. I was hoping this might whet their appetites for more, meaning that the tester might, just might, stick their toe into the genealogy waters😊

I’m hoping this article will help them get hooked! Maybe that’s you!

A Guide

This article can be read in one of two ways – as an overview, or, if you click the links, as a pretty thorough lesson. If you’re new, I strongly suggest reading it as an overview first, then a second time as a deeper dive. Use it as a guide to navigate your results as you get your feet wet.

I’ll be hotlinking to various articles I’ve written on lots of topics, so please take a look at details (eventually) by clicking on those links!

This article is meant as a guideline for what to do, and how to get started with your DNA matching results!

If you’re looking for ethnicity information, check out the First Glances article, plus here and here and here.

Concepts – Calculating Ethnicity Percentages provides you with guidelines for how to estimate your own ethnicity percentages based on your known genealogy and Ethnicity Testing – A Conundrum explains how ethnicity testing is done.

OK, let’s get started. Fun awaits!

The Goal

The goal for using DNA matching in genealogy depends on your interests.

  1. To discover cousins and family members that you don’t know. Some people are interested in finding and meeting relatives who might have known their grandparents or great-grandparents in the hope of discovering new family information or photos they didn’t know existed previously. I’ve been gifted with my great-grandparent’s pictures, so this strategy definitely works!
  2. To confirm ancestors. This approach presumes that you’ve done at least a little genealogy, enough to construct at least a rudimentary tree. Ancestors are “confirmed” when you DNA match multiple other people who descend from the same ancestor through multiple children. I wrote an article, Ancestors: What Constitutes Proof?, discussing how much evidence is enough to actually confirm an ancestor. Confirmation is based on a combination of both genealogical records and DNA matching and it varies depending on the circumstances.
  3. Adoptees and people with unknown parents seeking to discover the identities of those people aren’t initially looking at their own family tree – because they don’t have one yet. The genealogy of others can help them figure out the identity of those mystery people. I wrote about that technique in the article, Identifying Unknown Parents and Individuals Using DNA Matching.

DNAAdoption for Everyone

Educational resources for adoptees and non-adoptees alike can be found at www.dnaadoption.org. DNAAdoption is not just for adoptees and provides first rate education for everyone. They also provide trained and mentored search angels for adoptees who understand the search process along with the intricacies of navigating the emotional minefield of adoption and unknown parent searches.

First Look” classes for each vendor are free for everyone at DNAAdoption and are self-paced, downloadable onto your computer as a pdf file. Intro to DNA, Applied Autosomal DNA and Y DNA Basics classes are nominally priced at between $29 and $49 and I strongly recommend these. DNAAdoption is entirely non-profit, so your class fee or contribution supports their work. Additional resources can be found here and their 12 adoptee search steps here.

Ok, now let’s look at your results.

Matches are the Key

Regardless of your goal, your DNA matches are the key to finding answers, whether you want to make contact with close relatives, prove your more distant ancestors or you’re involved in an adoptee or unknown parent search.

Your DNA matches that of other people because each of you inherited a piece of DNA, called a segment, where many locations are identical. The length of that DNA segment is measured in centiMorgans and those locations are called SNPs, or single nucleotide polymorphisms. You can read about the definition of a centimorgan and how they are used in the article Concepts – CentiMorgans, SNPs and Pickin’Crab.

While the scientific details are great, they aren’t important initially. What is important is to understand that the more closely you match someone, the more closely you are related to them. You share more DNA with close relatives than more distant relatives.

For example, I share exactly half of my mother’s DNA, but only about 25% of each of my grandparents’ DNA. As the relationships move further back in time, I share less and less DNA with other people who descend from those same ancestors.

Informational Tools

Every vendor’s match page looks different, as was illustrated in the First Glances article, but regardless, you are looking for four basic pieces of information:

  • Who you match
  • How much DNA you share with your match
  • Who else you and your match share that DNA with, which suggests that you all share a common ancestor
  • Family trees to reveal the common ancestor between people who match each other

Every vendor has different ways of displaying this information, and not all vendors provide everything. For example, 23andMe does not support trees, although they allow you to link to one elsewhere. Ancestry does not provide a tool called a chromosome browser which allows you to see if you and others match on the same segment of DNA. Ancestry only tells you THAT you match, not HOW you match.

Each vendor has their strengths and shortcomings. As genealogists, we simply need to understand how to utilize the information available.

I’ll be using examples from all 4 major vendors:

Your matches are the most important information and everything else is based on those matches.

Family Tree DNA

I have tested many family members from both sides of my family at Family Tree DNA using the Family Finder autosomal test which makes my matches there incredibly useful because I can see which family members, in addition to me, my matches match.

Family Tree DNA assigns matches to maternal and paternal sides in a unique way, even if your parents haven’t tested, so long as some close relatives have tested. Let’s take a look.

First Steps Family Tree DNA matches.png

Sign on to your account and click to see your matches.

At the top of your Family Finder matches page, you’ll see three groups of things, shown below.

First Steps Family Tree DNA bucketing

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A row of tools at the top titled Chromosome Browser, In Common With and Not in Common With.

A second row of tabs that include All, Paternal, Maternal and Both. These are the maternal and paternal tabs I mentioned, meaning that I have a total of 4645 matches, 988 of which are from my paternal side and 847 of which are from my maternal side.

Family Tree DNA assigns people to these “buckets” based on matches with third cousins or closer if you have them attached in your tree. This is why it’s critical to have a tree and test close relatives, especially people from earlier generations like aunts, uncles, great-aunts/uncles and their children if they are no longer living.

If you have one or both parents that can test, that’s a wonderful boon because anyone who matches you and one of your parents is automatically bucketed, or phased (scientific term) to that parent’s side of the tree. However, at Family Tree DNA, it’s not required to have a parent test to have some matches assigned to maternal or paternal sides. You just need to test third cousins or closer and attach them to the proper place in your tree.

How does bucketing work?

Maternal or Paternal “Side” Assignment, aka Bucketing

If I match a maternal first cousin, Cheryl, for example, and we both match John Doe on the same segment, John Doe is automatically assigned to my maternal bucket with a little maternal icon placed beside the match.

First Steps Family Tree DNA match info

Click to enlarge

Every vendor provides an estimated or predicted relationship based on a combination of total centiMorgans and the longest contiguous matching segment. The actual “linked relationship” is calculated based on where this person resides in your tree.

The common surnames at far right are a very nice features, but not every tester provides that information. When the testers do include surnames at Family Tree DNA, common surnames are bolded. Other vendors have similar features.

People with trees are shown near their profile picture with a blue pedigree icon. Clicking on the pedigree icon will show you their ancestors. Your matches estimated relationship to you indicates how far back you should expect to share an ancestor.

For example, first cousins share grandparents. Second cousins share great-grandparents. In general, the further back in time your common ancestor, the less DNA you can be expected to share.

You can view relationship information in chart form in my article here or utilize DNAPainter tools, here, to see the various possibilities for the different match levels.

Clicking on the pedigree chart of your match will show you their tree. In my tree, I’ve connected my parents in their proper places, along with Cheryl and Don, mother’s first cousins. (Yes, they’ve given permission for me to utilize their results, so they aren’t always blurred in images.)

Cheryl and Don are my first cousins once removed, meaning my mother is their first cousin and I’m one generation further down the tree. I’m showing the amount of DNA that I share with each of them in red in the format of total DNA shared and longest unbroken segment, taken from the match list. So 382-53 means I share a total of 382 cM and 53 cM is the longest matching block.

First Steps Family Tree DNA tree.png

The Chromosome Browser

Utilizing the chromosome browser, I can see exactly where I match both Don and Cheryl. It’s obvious that I match them on at least some different pieces of my DNA, because the total and longest segment amounts are different.

The reason it’s important to test lots of close relatives is because even siblings inherit different pieces of DNA from their parents, and they don’t pass the same DNA to their offspring either – so in each generation the amount of shared DNA is probably reduced. I say probably because sometimes segments are passed entirely and sometimes not at all, which is how we “lose” our ancestors’ DNA over the generations.

Here’s a matching example utilizing a chromosome browser.

First Steps Family Tree DNA chromosome browser.png

I clicked the checkboxes to the left of both Cheryl and Don on the match page, then the Chromosome Browser button, and now you can see, above, on chromosomes 1-16 where I match Cheryl (blue) and Don (red.)

In this view, both Don and Cheryl are being compared to me, since I’m the one signed in to my account and viewing my DNA matches. Therefore, one of the bars at each chromosome represents Don’s DNA match to me and one represents Cheryl’s. Cheryl is the first person and Don is the second. Person match colors (red and blue) are assigned arbitrarily by the system.

My grandfather and Cheryl/Don’s father, Roscoe, were siblings.

You can see that on some segments, my grandfather and Roscoe inherited the same segment of DNA from their parents, because today, my mother gave me that exact same segment that I share with both Don and Cheryl. Those segments are exactly identical and shown in the black boxes.

The only way for us to share this DNA today is for us to have shared a common ancestor who gave it to two of their children who passed it on to their descendants who DNA tested today.

On other segments, in red boxes, I share part of the same segments of DNA with Cheryl and Don, but someone along the line didn’t inherit all of that segment. For example on chromosome 3, in the red box, you can see that I share more with Cheryl (blue) than Don (red.)

In other cases, I share with either Don or Cheryl, but Don and Cheryl didn’t inherit that same segment of DNA from their father, so I don’t share with both of them. Those are the areas where you see only blue or only red.

On chromosome 12, you can see where it looks like Don’s and Cheryl’s segments butt up against each other. The DNA was clearly divided there. Don received one piece and Cheryl got the other. That’s known as a crossover and you can read about crossovers here, if you’d like.

It’s important to be able to view segment information to be able to see how others match in order to identify which common ancestor that DNA came from.

In Common With

You can use the “In Common With” tool to see who you match in common with any match. My first 6 matches in common with Cheryl are shown below. Note that they are already all bucketed to my maternal side.

First Steps Family Tree DNA in common with

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You can click on up to 7 individuals in the check box at left to show them on the chromosome browser at once to see if they match you on common segments.

Each matching segment has its own history and may descend from a different ancestor in your common tree.

First Steps 7 match chromosome browser

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If combinations of people do match me on a common segment, because these matches are all on my maternal side, they are triangulated and we know they have to descend from a common ancestor, assuming the segment is large enough. You can read about the concept of triangulation here. Triangulation occurs when 3 or more people (who aren’t extremely closely related like parents or siblings) all match each other on the same reasonably sized segment of DNA.

If you want to download your matches and work through this process in a spreadsheet, that’s an option too.

Size Matters

Small segments can be identical by chance instead of identical by descent.

  • “Identical by chance” means that you accidentally match someone because your DNA on that segment has been combined from both parents and causes it to match another person, making the segment “looks like” it comes from a common ancestor, when it really doesn’t. When DNA is sequenced, both your mother and father’s strands are sequenced, meaning that there’s no way to determine which came from whom. Think of a street with Mom’s side and Dad’s side with identical addresses on the houses on both sides. I wrote about that here.
  • “Identical by descent” means that the DNA is identical because it actually descends from a common ancestor. I discussed that concept in the article, We Match, But Are We Related.

Generally, we only utilize 7cM (centiMorgan) segments and above because at that level, about half of the segments are identical by descent and about half are identical by chance, known as false positives. By the time we move above 15 cM, most, but not all, matches are legitimate. You can read about segment size and accuracy here.

Using “In Common With” and the Matrix

“In Common With” is about who shares DNA. You can select someone you match to see who else you BOTH match. Just because you match two other people doesn’t necessarily mean that it’s on the same segment of DNA. In fact, you could match one person from your mother’s side and the other person from your father’s side.

First Steps match matrix.png

In this example, you match Person B due to ancestor John Doe and Person C due to ancestor Susie Smith. However, Person B also matches person C, but due to ancestor William West that they share and you don’t.

This example shows you THAT they match, but not HOW they match.

The only way to assure that the matches between the three people above are due to the same ancestor is to look at the segments with a chromosome browser and compare all 3 people to each other. Finding 3 people who match on the same segment, from the same side of your tree means that (assuming a reasonably large segment) you share a common ancestor.

Family Tree DNA has a nice matrix function that allows you to see which of your matches also match each other.

First steps matrix link

click to enlarge

The important distinction between the matrix and the chromosome browser is that the chromosome browser shows you where your matches match you, but those matches could be from both sides of your tree, unless they are bucketed. The matrix shows you if your matches also match each other, which is a huge clue that they are probably from the same side of your tree.

First Steps Family Tree DNA matrix.png

A matrix match is a significant clue in terms of who descends from which ancestors. For example, I know, based on who Amy matches, and who she doesn’t match, that she descends from the Ferverda side and that Charles, Rex and Maxine descend from ancestors on the Miller side.

Looking in the chromosome browser, I can tell that Cheryl, Don, Amy and I match on some common segments.

Matching multiple people on the same segment that descends from a common ancestor is called triangulation.

Let’s take a look at the MyHeritage triangulation tool.

MyHeritage

Moving now to MyHeritage who provides us with an easy to use triangulation tool, we see the following when clicking on DNA matches on the DNA tab on the toolbar.

First Steps MyHeritage matches

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Cousin Cheryl is at MyHeritage too. By clicking on Review DNA Match, the purple button on the right, I can see who else I match in common with Cheryl, plus triangulation.

The list of people Cheryl and I both match is shown below, along with our relationships to each person.

First Steps MyHeritage triangulation

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I’ve selected 2 matches to illustrate.

The first match has a little purple icon to the right which means that Amy triangulates with me and Cheryl.

The second match, Rex, means that while we both match Rex, it’s not on the same segment. I know that without looking further because there is no triangulation button. We both match Rex, but Cheryl matches Rex on a different segment than I do.

Without additional genealogy work, using DNA alone, I can’t say whether or not Cheryl, Rex and I all share a common ancestor. As it turns out, we do. Rex is a known cousin who I tested. However, in an unknown situation, I would have to view the trees of those matches to make that determination.

Triangulation

Clicking on the purple triangulation icon for Amy shows me the segments that all 3 of us, me, Amy and Cheryl share in common as compared to me.

First Steps MyHeritage triangulation chromosome browser.png

Cheryl is red and Amy is yellow. The one segment bracketed with the rounded rectangle is the segment shared by all 3 of us.

Do we have a common ancestor? I know Cheryl and I do, but maybe I don’t know who Amy is. Let’s look at Amy’s tree which is also shown if I scroll down.

First Steps MyHeritage common ancestor.png

Amy didn’t have her tree built out far enough to show our common ancestor, but I immediately recognized the surname Ferveda found in her tree a couple of generations back. Darlene was the daughter of Donald Ferverda who was the son of Hiram Ferverda, my great-grandfather.

Hiram was the father of Cheryl’s father, Roscoe and my grandfather, John Ferverda.

First Steps Hiram Ferverda pedigree.png

Amy is my first cousin twice removed and that segment of DNA that I share with her is from either Hiram Ferverda or his wife Eva Miller.

Now, based on who else Amy matches, I can probably tell whether that segment descends from Hiram or Eva.

Viva triangulation!

Theory of Family Relativity

MyHeritage’s Theory of Family Relativity provides theories to people whose DNA matches regarding their common ancestor if MyHeritage can calculate how the 2 people are potentially related.

MyHeritage uses a combination of tools to make that connection, including:

  • DNA matches
  • Your tree
  • Your match’s tree
  • Other people’s trees at MyHeritage, FamilySearch and Geni if the common ancestor cannot be found in your tree compared against your DNA match’s MyHeritage
  • Documents in the MyHeritage data collection, such as census records, for example.

MyHeritage theory update

To view the Theories, click on the purple “View Theories” banner or “View theory” under the DNA match.

First Steps MyHeritage theory of relativity

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The theory is displayed in summary format first.

MyHeritage view full theory

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You can click on the “View Full Theory” to see the detail and sources about how MyHeritage calculated various paths. I have up to 5 different theories that utilize separate resources.

MyHeritage review match

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A wonderful aspect of this feature is that MyHeritage shows you exactly the information they utilized and calculates a confidence factor as well.

All theories should be viewed as exactly that and should be evaluated critically for accuracy, taking into consideration sources and documentation.

I wrote about using Theories of Relativity, with instructions, here and here.

I love this tool and find the Theories mostly accurate.

AncestryDNA

Ancestry doesn’t offer a chromosome browser or triangulation but does offer a tree view for people that you match, so long as you have a subscription. In the past, a special “Light” subscription for DNA only was available for approximately $49 per year that provided access to the trees of your DNA matches and other DNA-related features. You could not order online and had to call support, sometimes asking for a supervisor in order to purchase that reduced-cost subscription. The “Light” subscription did not provide access to anything outside of DNA results, meaning documents, etc. I don’t know if this is still available.

After signing on, click on DNA matches on the DNA tab on the toolbar.

You’ll see the following match list.

First Steps Ancestry matches

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I’ve tested twice at Ancestry, the second time when they moved to their new chip, so I’m my own highest match. Click on any match name to view more.

First Steps Ancestry shared matches

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You’ll see information about common ancestors if you have some in your trees, plus the amount of shared DNA along with a link to Shared Matches.

I found one of the same cousins at Ancestry whose match we were viewing at MyHeritage, so let’s see what her match to me at Ancestry looks like.

Below are my shared matches with that cousin. The notes to the right are mine, not provided by Ancestry. I make extensive use of the notes fields provided by the vendors.

First Steps Ancestry shared matches with cousin

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On your match list, you can click on any match, then on Shared Matches to see who you both match in common. While Ancestry provides no chromosome browser, you can see the amount of DNA that you share and trees, if any exist.

Let’s look at a tree comparison when a common ancestor can be detected in a tree within the past 7 generations.

First Steps Ancestry view ThruLines.png

What’s missing of course is that I can’t see how we match because there’s no chromosome browser, nor can I see if my matches match each other.

Stitched Trees

What I can see, if I click on “View ThruLines” above or ThruLines on the DNA Summary page on the main DNA tab is all of the people I match who Ancestry THINKS we descend from a common ancestor. This ancestor information isn’t always taken from either person’s tree.

For example, if my match hadn’t included Hiram Ferverda in her tree, Ancestry would use other people’s trees to “stitch them together” such that the tester is shown to be descended from a common ancestor with me. Sometimes these stitched trees are accurate and sometimes they are not, although they have improved since they were first released. I wrote about ThruLines here.

First Steps Ancestry ThruLines tree

click to enlarge

In closer generations, especially if you are looking to connect with cousins, tree matching is a very valuable tool. In the graphic above, you can see all of the cousins who descend from Hiram Ferverda who have tested and DNA match to me. These DNA matches to me either descend from Hiram according to their trees, or Ancestry believes they descend from Hiram based on other people’s trees.

With more distant ancestors, other people’s trees are increasingly likely to be copied with no sources, so take them with a very large grain of salt (perchance the entire salt lick.) I use ThruLines as hints, not gospel, especially the further back in time the common ancestor. I wish they reached back another couple of generations. They are great hints and they end with the 7th generation where my brick walls tend to begin!

23andMe

I haven’t mentioned 23andMe yet in this article. Genealogists do test there, especially adoptees who need to fish in every pond.

23andMe is often the 4th choice of the major 4 vendors for genealogy due to the following challenges:

  • No tree support, other than allowing you to link to a tree at FamilySearch or elsewhere. This means no tree matching.
  • Less than 2000 matches, meaning that every person is limited to a maximum of 2000 matches, minus however many of those 2000 don’t opt-in for genealogical matching. Given that 23andMe’s focus is increasingly health, my number of matches continues to decrease and is currently just over 1500. The good news is that those 1500 are my highest, meaning closest matches. The bad news is the genealogy is not 23andMe’s focus.

If you are an adoptee, a die-hard genealogist or specifically interested in ethnicity, then test at 23andMe. Otherwise all three of the other vendors would be better choices.

However, like the other vendors, 23andMe does have some features that are unique.

Their ethnicity predictions are acknowledged to be excellent. Ethnicity at 23andMe is called Ancestry Composition, and you’ll see that immediately when you sign in to your account.

First Steps 23andMe DNA Relatives.png

Your matches at 23andMe are found under DNA Relatives.

First Steps 23andMe tools

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At left, you’ll find filters and the search box.

Mom’s and Dad’s side filter matches if you’ve tested your parents, but it’s not like the Family Tree DNA bucketing that provides maternal and paternal side bucketing by utilizing through third cousins if your parents aren’t available for testing.

Family names aren’t your family names, but the top family names that match to you. Guess what my highest name is? Smith.

However, Ancestor Birthplaces are quite useful because you can sort by country. For example, my mother’s grandfather Ferverda was born in the Netherlands.

First Steps 23andMe country.png

If I click on Netherlands, I can see my 5 matches with ancestors born in the Netherlands. Of course, this doesn’t mean that I match because of my match’s Dutch ancestors, but it does provide me with a place to look for a common ancestor and I can proceed by seeing who I match in common with those matches. Unfortunately, without trees we’re left to rely on ancestor birthplaces and family surnames, if my matches have entered that information.

One of my Dutch matches also matches my Ferverda cousin. Given that connection, and that the Ferverda family immigrated from Holland in 1868, that’s a starting point.

MyHeritage has a similar features and they are much more prevalent in Europe.

By clicking on my Ferverda cousin, I can view the DNA we share, who we match in common, our common ethnicity and more. I have the option of comparing multiple people in the chromosome browser by clicking on “View DNA Comparison” and then selecting who I wish to compare.

First Steps 23andMe view DNA Comparison.png

By scrolling down instead of clicking on View DNA Comparison, I can view where my Ferverda cousin matches me on my chromosomes, shown below.

First STeps 23andMe chromosome browser.png

23andMe identifies completely identical segments which would be painted in dark purple, the legend at bottom left.

Adoptees love this feature because it would immediately differentiate between half and full siblings. Full siblings share approximately 25% of the exact DNA on both their maternal and paternal strands of DNA, while half siblings only share the DNA from one parent – assuming their parents aren’t closely related. I share no completely identical DNA with my Ferverda cousin, so no segments are painted dark purple.

23andMe and Ancestry Maps Show Where Your Matches Live

Another reason that adoptees and people searching for birth parents or unknown relatives like 23andMe is because of the map function.

After clicking on DNA Relatives, click on the Map function at the top of the page which displays the following map.

First Steps 23andMe map

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This isn’t a map of where your matches ancestors lived, but is where your matches THEMSELVES live. Furthermore, you can zoom in, click on the button and it displays the name of the individual and the city where they live or whatever they entered in the location field.

First Steps 23andMe your location on map.png

I entered a location in my profile and confirmed that the location indeed displays on my match’s maps by signing on to another family member’s account. What I saw is the display above. I’d wager that most testers don’t realize that their home location and photo, if entered, is being displayed to their matches.

I think sharing my ancestors’ locations is a wonderful, helpful, idea, but there is absolutely no reason whatsoever for anyone to know where I live and I feel it’s stalker-creepy and a safety risk.

First Steps 23andMe questions.png

If you enter a location in this field in your profile, it displays on the map.

If you test with 23andMe and you don’t want your location to display on this map to your matches, don’t answer any question that asks you where you call home or anything similar. I never answer any questions at 23andMe. They are known for asking you the same question repeatedly, in multiple locations and ways, until you relent and answer.

Ancestry has a similar map feature and they’ve also begun to ask you questions that are unrelated to genealogy.

Ancestry Map Shows Where Your Matches Live

At Ancestry, when you click to see your DNA matches, look to the right at the map link.

First Steps Ancestry map link.png

By clicking on this link, you can see the locations that people have entered into their profile.

First Steps Ancestry match map.png

As you can see, above, I don’t have a location entered and I am prompted for one. Note that Ancestry does specifically say that this location will be shown to your matches.

You can click on the Ancestry Profile link here, or go to your Personal Profile by click the dropdown under your user name in the upper right hand corner of any page.

This is important because if you DON’T want your location to show, you need to be sure there is nothing entered in the location field.

First Steps Ancestry profile.png

Under your profile, click “Edit.”

First Steps Ancestry edit profile.png

After clicking edit, complete the information you wish to have public or remove the information you do not.

First Steps Ancestry location in profile.png

Sometimes Your Answer is a Little More Complicated

This is a First Steps article. Sometimes the answer you seek might be a little more complicated. That’s why there are specialists who deal with this all day, everyday.

What issues might be more complex?

If you’re just starting out, don’t worry about these things for now. Just know when you run into something more complex or that doesn’t make sense, I’m here and so are others. Here’s a link to my Help page.

Getting Started

What do you need to get started?

  • You need to take a DNA test, or more specifically, multiple DNA tests. You can test at Ancestry or 23andMe and transfer your results to both Family Tree DNA and MyHeritage, or you can test directly at all vendors.

Neither Ancestry nor 23andMe accept uploads, meaning other vendors tests, but both MyHeritage and Family Tree DNA accept most file versions. Instructions for how to download and upload your DNA results are found below, by vendor:

Both MyHeritage and Family Tree DNA charge a minimal fee to unlock their advanced features such as chromosome browsers and ethnicity if you upload transfer files, but it’s less costly in both cases than testing directly. However, if you want the MyHeritage DNA plus Health or the Family Tree DNA Y DNA or Mitochondrial DNA tests, you must test directly at those companies for those tests.

  • It’s not required, but it would be in your best interest to build as much of a tree at all three vendors as you can. Every little bit helps.

Your first tree-building step should be to record what your family knows about your grandparents and great-grandparents, aunts and uncles. Here’s what my first step attempt looked like. It’s cringe-worthy now, but everyone has to start someplace. Just do it!

You can build a tree at either Ancestry or MyHeritage and download your tree for uploading at the other vendors. Or, you can build the tree using genealogy software on your computer and upload to all 3 places. I maintain my primary tree on my computer using RootsMagic. There are many options. MyHeritage even provides free tree builder software.

Both Ancestry and MyHeritage offer research/data subscriptions that provide you with hints to historical documents that increase what you know about your ancestors. The MyHeritage subscription can be tried for free. I have full subscriptions to both Ancestry and MyHeritage because they both include documents in their collections that the other does not.

Please be aware that document suggestions are hints and each one needs to be evaluated in the context of what you know and what’s reasonable. For example, if your ancestor was born in 1750, they are not included in the 1900 census, nor do women have children at age 70. People do have exactly the same names. FindAGrave information is entered by humans and is not always accurate. Just sayin’…

Evaluate critically and skeptically.

Ok, Let’s Go!

When your DNA results are ready, sign on to each vendor, look at your matches and use this article to begin to feel your way around. It’s exciting and the promise is immense. Feel free to share the link to this article on social media or with anyone else who might need help.

You are the cumulative product of your ancestors. What better way to get to know them than through their DNA that’s shared between you and your cousins!

What can you discover today?

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Disclosure

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

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Services

Genealogy Research

Concepts – Relationship Predictions

One of the ways people utilize autosomal DNA for genealogical matching is by looking for common segments of DNA that match with known, or unknown, relatives.  When the relationship to the person is unknown, we attempt to utilize how much DNA we share with that person as a predictor of how, or at what level, we’re related to them – so in essence where or how far back we might look in our tree for a common ancestor.

Until recently, the best estimate we had in terms of how much DNA someone of a particular relationship (like first cousin) could be expected to share both in terms of percentages and also cMs (centiMorgans) of DNA was the table on the ISOGG wiki page.  Often, these expected averages didn’t mesh well with what the community was seeing in reality.

Recently, Blaine Bettinger’s crowdsourced Shared cM Project reported the averages for each relationship level, plus the range represented from lowest to highest in a project where more than 10,000 people participated by providing match information.

Additionally, before publication, Blaine worked with a statistician to remove outliers in each category that might represent data entry errors, etc. Not only did Blaine write a nice blog article about this latest data release, he also wrote a corresponding paper that is downloadable that includes tables and histograms not in his blog.

I am constantly looking between the two sources, meaning the ISOGG table and Blaine’s paper, so as an effort in self-preservation, I combined the information I use routinely from the two tables – and did some analysis in the process.  Let’s take a look.

The Combined Expected cM and Actual Shared cM Chart

On the chart below, the two yellow headed columns are the Expected Shared cMs from the ISOGG table and Blaine’s Shared cM Average – which is the average amount of DNA that was actually found. These, along with the percent of shared DNA are the columns I use most often, followed by Blaine’s minimum and maximum which are the ranges of matching DNA found for each category.  As it turns out, the range is incredibly important – perhaps more important than the averages expected or reported – because the ranges are what we actually see in real life.

I’ve also included the number of respondents, because categories with a larger number of respondents are more likely to be more accurate than categories with only a few, like great-great-aunt/uncle with only 6.

It’s interesting that the greatest number of respondents fell into the aunts/uncles niece/nephew category with second cousins once removed a very close contender.

These were followed by the next closest categories being, in order; first cousins, second cousins, first cousins once removed, second cousins once removed and third cousins.

Note:  If you downloaded this chart on August 4, 2016, there was an error in the maximum number of first cousins trice removed.  On August 5, 2016, it was corrected to read 413.

Expected vs shared cM 4

You can see that in reality, all categories except two produced larger than the expected cM value. One category was equal and one was smaller (yes I checked to be sure I hadn’t transcribed incorrectly). Actual numbers with higher values are peach colored, lower is green and white is equal.

Most averages aren’t dramatically different for close relationships, but as you move further out, the difference in the averages is significantly greater.  Beginning with third cousins once removed, and every category below that in the chart, the actual average is more than twice that of the expected average.  In addition, the ranges for all categories are wider than expected, especially the further out you go in terms of relationships.

We often wonder why the relationship predictions, especially beyond first or second cousins vary so widely at the testing companies and GedMatch. In the chart above, you can see that beyond first cousins, the ranges begin to overlap.

Ranges of the same relationship degree should share the same percentages and theoretically, the same amounts of DNA, but they don’t. You can see that the cells marked in red are all 4th degree relatives.  However, half first cousins show a maximum of 580, with the two following rows showing 704 and 580 – all 4th degree relatives. There’s a pretty significant difference between 580 and 704.

Through 5th degree relatives, everyone matched at some level, meaning the minimum is above zero, but beginning with 6th degree relatives, row highlighted in yellow, some people did not match relatives at that level, meaning the minimum is zero.

In the last 4 rows on the chart, 15th, 16th and 17th degree relatives, marked with light aqua, where academically we “should” share 0% of our DNA, we see that the observed average is from 7 to 11 cM and the range is up to 29 cM.

An example of why predictions are so difficult is that if you are on the high end of the 4th cousins range, a 9th degree relative with 91 shared cMs of DNA, you are also right at the average between 6th and 7th degree relatives which fall into the half second cousin or third cousin range.

Without relationship knowledge, the vendor, based on averages, is going to call this relationship a 2nd or 3rd cousin, when in reality, it’s a 4th cousin. Most vendor relationship predictions are based on a combination of total shared cMs and longest block, but still, it’s easy to be outside the norm.  In other words, not only does one size not fit all, it probably doesn’t fit most.

Graphs

For me, graphs help make information understandable because I can see the visual comparison.

These overlapping ranges are much easier to visualize using charts.  Please note that you can click on any image for a larger view.

Expected full range 4

The values and ranges for 1st, 2nd and 3rd degree relatives are so much larger than more distant relatives, that you can’t effectively see the information for more distant relatives, so I’ve broken the charts apart, below.

Expected to third degree

This first chart, above, shows third degree relatives and closer.  Note that the purple maximum for aunts/uncles, nieces/nephews is larger than the minimum for full siblings and greater than the red average or blue expected for half-siblings.

expected 4th to 17th 4

This second chart shows the more distant relationships, meaning 4th degree through 17th degree relatives, but the more distant relationships are still difficult to see, so let’s switch to bar charts and smaller groups.

Expected stacked to third

This first bar chart includes parent/child through first cousins relationships, or 1st through 3rd degree relatives. You can see that the first cousin maximum range (purple) overlaps the aunt/uncle, grandparents and half-sibling minimum ranges (green.) Half sibling max and full sibling minimum are very close.

Expected 4th to 17th stacked 4

The balance of relationships are a bit small to view in one chart, but the ranges do overlap significantly.  Unfortunately, Excel does us the favor of skipping some labels on the left side of the chart.

Expected 4th to 17th no legend 4

Removing the legend helps a bit, but not much.  Please refer to the color legend in the same graph above.  I’ve further divided the groups below.

Expected 4th to 9th 4

The chart above shows 4th degree to 9th degree relatives, meaning great-great-aunts or uncles through 4th cousins.

expected 4th to 9th no legend 4

The same chart, above, with the legend removed to allow for more viewing space.  You’ll notice that at the half second cousins level, and more distant, the green minimum disappears, which means that some people have no matches, so the minimum cM shared is zero for some people with this relationship level.  However, based on the average and maximum, many people do share DNA with people at that relationship level.

Expected 7th to 17th 4

The chart above begins with 7th degree relatives, half second cousins, where you share less than 1% of your DNA.

In many cases, the purple maximum range for one relationship category overlaps Blaine’s average and the expected values for other categories.  For example, in the chart below, you can see that the maximum purple bar for the various 5th cousin ranges is higher than the third cousin, twice removed red shared cM average, and significantly higher than the blue expected shared cM value.  In fact, the 6th cousin purple max is nearly the same as the blue expected cM for third cousins once removed.  Note that Excel showed only every other category on the left hand axis, so you’ll need to refer to the actual data chart from time to time.

expected 7th to 17th no legend

I’ve removed the legend again so you can see the actual stacked ranges more clearly.  All of the 7th degree relatives have a minimum of zero, so there is no green bar.  Furthermore, at 5th cousins twice removed, the expected shared cMs drops to below 1, so the blue bar is nearly indistinguishable.

expected 9th to 17th

This last chart shows the smallest group, 9th through 17th degrees, or 4th through 8th cousins.

expected 9th to 17th no legend

On this final chart, we clearly see that Blaine’s actual red shared cMs and the purple maximum are significantly more pronounced than the blue expected shared cMs.  Some people share no DNA at this level, which is to be expected, but a non-trivial number of people share significantly more than is mathematically expected.  There are no absolutes.

Summary

DNA is not always inherited in the fashion or amount expected, and that wide variance is why we see what people believe are “false positive” relationship predictions. In reality, the best the vendors can do is to work with the averages.  This also explains why it’s so difficult for us to estimate or determine how a person might be connected based just on the relationship or generational prediction.  It’s just that, a prediction based on averages which may or may not reflect reality.

There’s a lot we don’t know yet about inheritance – why certain segments are passed on, often intact, sometimes for many generations, and some segments are not.  We don’t know how segments are “selected” for inheritance and we don’t yet know why some segments appear to be “sticky” meaning they show up more in descendants than other segments.

Close relationships are relatively easy, or easier, to predict, at least by relationship degree, but further distant ones are almost impossible to predict accurately based on either academic inheritance models or Blaine’s crowdsourced average cM information.

Here’s a clean copy of the combined chart for your use.

Note:  If you downloaded this chart on August 4, 2016, there was an error in the maximum number of first cousins trice removed.  On August 5, 2016, it was corrected to read 413.

Expected vs shared clean 4

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Disclosure

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

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Services

Genealogy Research

Demystifying Ancestry’s Relationship Predictions Inspires New Relationship Estimator Tool

Today, I’m extremely pleased to bring you a wonderful guest article written by Karin Corbeil as spokesperson for a very fine group of researchers at www.dnaadoption.com.

I love it when citizen science really works, pushes the envelope, makes discoveries and then the scientists develop new tools!  This is a win-win for everyone in the genetic genealogy community – not just adoptees!  I want to say a very big thank you to this wonderful team for their fine work.

Take it away Karin….

As genetic genealogists we are always looking for a better “mousetrap”.  Tools and analyses that can better help us understand what we are actually looking at with our DNA results.  For adoptees and those with unknown ancestors it can be even more important.

When Ancestry came out with their “New Amount of Shared DNA” an explanation was necessary to understand what we were seeing.

We at DNAAdoption are asked to explain over and over again why your half-sibling was predicted as a 1st cousin, or that predicted Close Family – 1st cousin could actually be a half-nephew, or a predicted 3rd cousin could be a 4th cousin.  Ancestry doesn’t provide the detailed information needed to support their predicted relationship categories so providing the explanations was often a struggle.

We knew that you cannot draw or correlate any relationship inferences from either the total amount of shared DNA or the number of segments from the typical tools utilized by genetic genealogists because Ancestry’s totals will be lower and their segments will be broken into more pieces due to the removal of segments identified by the Timber algorithm as invalid matches.[1]

So in order to get a better reference to how predictions are set by Ancestry, we at DNAAdoption gathered data from 1,122 matches of different testers who had confirmed these matches as specific relationships. A collaborative effort was led by Richard Weiss of the DNAAdoption team.  Richard worked his magic with the data and the results are presented here.

A clip of the Pivot table from the data input:

Ancestry relationship table

The full data spreadsheet can be downloaded here:

Ancestry Predictions vs. Actual Relationships

Ancestry Predictions vs actual relationships

The most interesting thing about some of the prediction vs the actual relationships was seeing how more distant relationships can vary so greatly. Look at the 4th cousin prediction, for example. This varies from a half 1st cousin once removed to an 8th cousin once removed. (Obviously, this confirmed 8th cousin once removed probably has a persistent or intact segment that, due to the randomness of DNA down the generations, persisted for many generations). This makes it extremely difficult to assess any predicted relationship at the 4th cousin level. Even 1st, 2nd and 3rd cousin predictions had wide variances.

The only conclusion we can draw from this is to use Ancestry predictions with extreme caution.

With this data we were then able to take the numbers and add to our DNA Prediction Chart that we use in our DNA classes at DNAAdoption.

DNA Prediction Chart

DNA Prediction Chart 2

The full Excel spreadsheet can be downloaded here.

We then incorporated this data into our Relationship Estimator Tool created by Jon Masterson.

Jon explains, “This small program is intended to make the DNA Prediction Chart Spreadsheet a bit easier to use. It is based entirely on the data in this spreadsheet plus some interpolation of missing values. The algorithm to determine the most likely relationship(s) is very simple and based on summing the score of valid entries in the table for a given input. It is very much an experiment and test. It is likely to be less accurate with close relationships where there is missing data in the spreadsheet. You can also save the match information that you generate.”

First, download the zip file RelationshipEstimator.zip here.

Extract the files from the zip file and run the RelationshipEstimator.exe

relationship estimator

The following results are for the same person who has been confirmed as a 3rd cousin. The first set of data is from Gedmatch, the second set is from Ancestry. With this match the actual total cMs over 5 cMs are 122.9 with 5 segments; the same person shows Ancestry Shared DNA of 112 cMs with 7 segments.

For 23andMe/FTDNA/Gedmatch add the individual segment lengths in the first box using a slash “/” between each number.

At the “Source” box select 23andMe/FTDNA/Gedmatch, then click the “Process” button. Several possible estimated relationships will show.

Relationship estimator 2

For Ancestry, enter the total cMs, the # of segments.  At the “Source” box select “Ancestry”, then “Process”.

Relationship estimator 3

More information about this tool can be found here.

By seeing the larger variances with the Ancestry data (6 estimated relationships vs 3 for the actual Gedmatch data) we can only encourage those on Ancestry to upload your raw data file to Gedmatch. Of course, we still hope that one day Ancestry will release the full segment data in a chromosome browser.

We at DNAAdoption continue to try and provide analyses and tools, many times in cooperation with DNAGedcom, to give those searching for their roots better information. But we are “not for adoptees only” and provide this information for the genetic genealogy community as a whole.  We plan to add more data to these analyses in the near future.  We hope you will find it useful.

Your questions and comments are welcome.

Karin Corbeil (karincorbeil@gmail.com)

Diane Harman-Hoog (harmanhoog@gmail.com)

Richard Weiss (rnlweiss@gmail.com)

Jon Masterson (jon@scruffyduck.co.uk) 

[1] Roberta Estes, paraphrased from  http://dna-explained.com/2015/11/06/ancestrys-new-amount-of-shared-dna-what-does-it-really-mean/

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Disclosure

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

Thank you so much.

DNA Purchases and Free Transfers

Genealogy Services

Genealogy Research