Find AncestryDNA Matches with Common Ancestors

A Segment-ology TIDBIT

Disclaimer 1 – This is a search methodology, and may not zero in on your Ancestor  100% of the time.

Disclaimer 2 – This process works down to the lowest cM and any generation. There is NO guarantee that the DNA segments are linked to any Common Ancestor found, or that the Common Ancestors found are accurate. This is just a clue.

This process uses AncestryDNA’s search function to find DNA Matches with Trees that have your specified surname/location in them. From my perspective this is a pretty powerful search technique. The results are a list of your DNA Matches (so you share some DNA with each one); and each Match has a Tree large enough to have the surname and birth place combination you specify in them. I’ve found a high percentage of these results to be my Ancestors. We must still verify both our path and the Match’s patch back to the CA. And, if we want to use the DNA segment, we must still verify that that segment is from that CA.


  1. At AncestryDNA, click on DNA (in the upper tool bar) and DNA Matches (from the drop down menu) – the result is the entire list of your DNA Matches.
  2. Click on Search (on the right side; just above your Match list) – this brings up 3 search boxes.
  3. Type a Surname in the “Surname in Matches’ trees” box; AND type a location in the “Birth location in Matches’ trees” box. Ex: CHEATHAM and Henrico County, Virginia, USA [This is one of my 7xGreat grandparents – I should get mostly 8C Matches with this search]. Use the “Include similar surnames” check box per your judgment. It’s best to use the Ancestry standards for the location, which will usually come up as a suggestion as you type.
  4. Click on the green Search button – the resulting list will be your DNA Matches who meet the criteria.
  5. Click on any Match to get their page (compared to you). You can investigate your target surname from the Shared Surnames list OR by clicking on their Linked (or Unlinked) Tree and search for that Surname.

Like all search processes, the key is finding the right combination of search terms. Clearly searching on JONES in Virginia, USA would not be helpful. My best suggestion is to search on a County, State combination.

I started with a list of my 7xGreat grandparents with their birth places. Most of these surname/birthplace combinations give me a very useful list, which often includes Matches with closer CAs (same surname and county). I can easily skip over all the ones I’ve already found and “Stared”, “Dotted”, and “Noted” – but many are new to me (ThruLines does not include any Matches beyond 6C). Also, many of the Matches with these CAs will share small DNA Segments – but they may be true genealogy cousins anyway.

If you get into a “grove” with this process, try using surnames from married daughters of your Ancestor (with the appropriate birth location). You’ll find even more Matches who had not taken their Tree back far enough…

This process ties into Triangulated Groups and/or (manual) Clustering, in that it finds more CAs to add to your Notes. You can then click on Shared Matches to see if this information would influence a Cluster or TG. By “influence” I mean that it could reinforce existing information seen in the Shared Matches, it could add evidence to extend an existing CA or Ancestral line, or it could contradict existing information resulting in a review of that TG or Cluster.

Also, if you are trying to “Dot” some of your 6-7cM Matches, this process will focus on some key Matches. When your Match list (for a surname/location) comes up, just scroll down and work up from the bottom until you’re into the 8cM Matches…

More Common Ancestors are good! They help validate the genealogy and add clues for Triangulated Groups and/or Clusters.


[AV] Segment-ology: Find AncestryDNA Matches with Common Ancestors TIDBIT by Jim Bartlett 20200808

Use Clusters!

Clusters form on a Common Ancestor (CA). We don’t have proof of this but a) it makes sense (why else would our Matches match each other in a Cluster?); and b) it sure seems to work (I’ve found many new CAs with Matches, just by focusing on the CA in a Cluster).

So, with this concept in mind, let’s use our Clusters!

  1. Known CA – If you *know*, or even suspect, the CA of a Cluster, search other Matches in that Cluster for that CA or location or a collateral line. If a Cluster Match has a good Tree, there’s a good chance you’ll find the CA in their Tree. There’s a good chance multiple Matches in a Cluster will all have the same CA. Armed with a known CA, I’ve often been able to build out a Match’s Tree to that CA.
  2. Unknown CA – If you don’t have a clue to the Cluster CA, find the most likely CA among the Matches – whether you have that surname or not. Let the Matches tell you the Cluster CA – per this blogpost. This is also effective for Brick Walls and unknown parentage.
  3. Suspect CA – If some on the internet propose an Ancestor for one of your lines without proof, or if you are suspicious of their “proof”, test out that Ancestor. Look for that surname among the Matches in appropriate Clusters. “Appropriate” means these Clusters are probably on that line. Try the Unknown CA process and see if this same surname comes up. Clearly, if many people have bought into this Suspect CA, this process won’t work (however, then using this process with the Suspect CA’s mother’s surname, may be helpful). Example: During 40 years of research on my NEWLON line, many had heard the claim by one researcher that a spouse was “Martha JANNEY”, but without proof, few used that information. So I decided to test it. Virtually none of my Cluster Matches had the JANNEY surname; but many had the CUMMIN/GS surname. In fact, searching all of my DNA Matches (over 125,000 of them) turned up 17 Matches (down to 6cM) with the JANNEY surname in Loudoun Co, VA – none in any of my “appropriate” Clusters.

Bottom line: Use the concept that Clusters form on a CA. Use it to find CAs with more Matches; Use it to break through Brick Walls or explore Clusters without a CA. Use it to *test* likely or suspicious surnames in selected Clusters – if the CA is correct, it should show up in multiple Matches in a Cluster.


[19J] Segment-ology: Use Clusters! by Jim Bartlett 20200705

Easy Manual Clustering at AncestryDNA

Auto-Clustering at AncestryDNA is in a pause mode now. But we can still look at and analyze our own Matches any way we want. We can even form our own Clusters. Here is a modest process that may produce Clusters that are very helpful to us. AncestryDNA does not provide segment information that would allow grouping by Triangulated Groups, so Clustering is the best way to group Matches. And there are several advantages to using Clusters.

Manual Clustering Process at AncestryDNA

  1. Start with your ThruLines. These are Matches who share a Common Ancestor (usually a couple) with us. The ThruLines process looks for obvious CAs; it looks in Private (but searchable) Trees for CAs; it sometimes “fills in the blanks” with information from other (even non-DNA Match) Trees to create a link between you and a DNA Match back to a CA. This ‘fill in the blanks” process may be in your Tree or your Match’s Tree or both. The ThruLines process works out to 5xG grandparents on both sides – if either side is more than 7 generations back, it will not be reported. In any case, you should review the information provided by Ancestry and decide if the ThruLines CA is correct, or not.
  2. Enter the CA information in your Match’s Note box [see “Add note”] – I use a combination of Ahnentafel Number/side; relationship; and surnames. Example: A0140P/6C: WELCH/SPENCE – the Match and I are 6C, sharing ancestors Sylvester WELCH Jr and Anne SPENCE; Sylvester WELCH is my Ahnentafel Number 140 on my Paternal side. I like using Ahnentafel numbers as they are easy to compare and determine relationships. Just divide by 2 to get 140>70>35>17>8>4>2>1 (me), so A0008P/2C: BARTLETT/NEWLON is on this same ancestral line. Do this for all your valid or suspected* ThruLines CAs. NB: Some Matches will share more than one CA with you – enter them both.         [* I include suspected ThruLines CAs – if they are incorrect, they almost never Cluster and can thus be culled out.]  Anyway – use whatever system works for you, just enter something in the Note box. You’ll be looking at these Notes of Shared Matches to form Clusters, and you want to know who shares the same CA.
  1. After going one or all the ThruLines CAs, call up one of these Matches and review their Shared Matches. I count the number of SMs and the number on the same ancestral line, and record this in the Note box. Example: SM: 17/25xA0140P. This means that out of 25 total Shared Matches, 17 of them had a Note indicating A0140P CA. NB a Shared Match with a Note indicating A0070P would be included. A SM with A0034P would also be included because 34P is really a short cut for 34P/35P, and 35P is in the same ancestral line. Likewise, 8P is in the same ancestral line and would be counted as also having A0140P ancestry. Repeat for all ThruLines Matches. It doesn’t take that long for such a powerful tool as Clustering.
  2. Use judgement to decide who is in a Cluster. In some cases, it’s crystal clear – virtually every Shared Match has an “SM: note” with the same CA. Other cases are not so clear, so you need to decide if there is sufficient evidence to include a Match in a Cluster. In some cases, a Match with a ThruLines CA will actually have several Shared Matches with a “different CA” – the Clustering process dictates such a Match be Clustered with the Matches with a “different CA”. And I would certainly review that Match again to see if there isn’t some clue that indicates the “different CA” is in their tree, too.
  3. Cluster ID – you can use any system you want to name your Clusters. One way is CL001 to CL200. Another way is to use the CA – Example: CL0140P1. This is the Ahnentafel Number preceeded by CL. NB: I added a 1 at the end because some of your Ancestors may be linked to more than one Cluster. [I have Ancestor A0556M, a 7xG grandparent couple, who are in three large Clusters.] Add this Cluster ID to the Match notes. Example A0170P-CL047/6C: WELCH/SPENCE. Or use whatever system you want.
  4. Once you have determined Clusters based on ThruLines Matches and CAs, you can go back and look at a Match in a Cluster and look at his/her Shared Matches who aren’t in a Cluster. Do some have several Shared Matches themselves who are in a Cluster? If so, add these Shared Matches to the Cluster. NB: You can also look at Matches under 20cM – many of them have Shared Matches. If several Shared Matches are in one particular Cluster, add the under 20cM Match to the Cluster.

Clusters are one of the best tools I’ve found for grouping AncestryDNA Matches and finding more CAs.


[19I] Segment-ology: Easy Manual Clustering at AncestryDNA by Jim Bartlett 20200701

Let the Matches Tell Us the Cluster Common Ancestor

Using a 20cM threshold at AncestryDNA, I got 156 Clusters. That’s roughly one Cluster for each of my 128 5xG grandparents – or two Clusters per 5xG grandparent couples – often with valuable Common Ancestor (CA) hints from ThruLines. I don’t know 50 of my 128 5xG grandparents (they are brick walled) – so I would expect (50×156/128=) 61 of my 156 clusters to be blank. What’s a body to do?

Well… in the first place the above calculation is based on finding a CA at the 5xG grandparent level. ThruLines provides clues for all the Ancestors I know – but, clearly, they cannot help with Clusters (or TGs) beyond a brick wall. For almost all of the Clusters, I know the parent; and for roughly 80% I know the grandparent; and for many I know the CA out to the brick wall. So I’ve got a start. But, for many of my Clusters, there is very little otherwise to go on – just a lot of Matches in a Cluster. What’s a body to do?

As I’ve said before, let’s think about lemonade…  In my last post (Using a Group Ancestor), I noted that grouping (segment Triangulation and Shared Match Clustering) results in a group of Matches with the same Common Ancestor (CA). This is the concept, even if we don’t have any clue as to who the CA is. But let’s make “the certainty that there is a CA” work for us… Let’s have the Matches tell us who the CA is for a Cluster. Seems like lemonade to me.

Here is a process for AncestryDNA: [I hope you’ve saved your last Cluster report]

  1. Select a large Cluster for which you have no known CAs (or only a few which are in conflict with each other).
  2. Make a spreadsheet with three columns: Match Name and Surnames and Notes.
  3. Select a Match in the Cluster who has a Tree with more than 99 people.
  4. Type the Match name in the spreadsheet.
  5. Go to that Match in AncestryDNA (either from the URL in the Cluster; or by searching AncestryDNA).
  6. Type the surnames for that Match (both Shared Surnames & Match’s Tree Only) in Surname column.
  7. Copy the Match name down the spreadsheet for each surname.
  8. Repeat for each Match in the Cluster with a Tree over 99 people.
  9. Sort the spreadsheet on the Surname column.
  10. Scroll down the list and highlight likely Surname groups [it would be great to find a clear winner – repeated multiple times. If not pick the top few surnames].
  11. Go back to the Matches with most likely surname(s) and put in the Notes column the Patriarch or any other identifying information (birth, location, ethnicity, etc). The expectation (hope) is that you’ll find a Common Ancestor or two in this process.

I can almost hear the collective groan at step #6. Yes, it’s an onerous task. I sat down with a favorite beverage and typed non-stop the 660 surnames for Matches in one Cluster; 750 in another Cluster. But, think about this another way: would you spend a half-day of work to find a new Ancestor? That would be a nice glass of lemonade.

In my first Cluster try, I found three Surnames (ADAMS, CAUDILL and CRAFT) repeated several times. A quick and dirty Tree quickly determined John ADAMS married 1769 Loudoun Co, VA Nancy CAUDILL; and their daughter, Elizabeth married Archelous CRAFT – and 5 of my Matches in the Cluster descended from these two couples!! I already had some clues that this Cluster was on my father’s father’s side. This includes my NEWLON line which had a brick wall born c1774 Loudon Co, VA which I determined was Susan CUMMINGS – blogpost here. Her father is strongly suspected to be John CUMMINGS born c1746, but nothing is known about John’s first wife, the mother of Susan CUMMINGS and my Ancestor – a new brick wall. If John’s first wife was an ADAMS, all of this would fall into place as a hypothesis.

By the nature of Shared Match Clustering, this Cluster must have a CA. With five widely separated Matches agreeing on the same CA (and no other surnames turning out any hints at all), I think this is a strong clue. But, more research is needed.

The other Cluster had several repeated surnames, but none that I have been able to link together, yet. I may drop down and look at the surnames of Matches with Trees in the 50-99 people range… maybe another hour of typing… If I find a clue it will all be worth while.

Bottom Line: A Cluster (or a TG) has a CA. The Matches in a Cluster should all share this CA. Let the Matches Tell Us the Cluster Common Ancestor.  The process above is one way to do this. A particular advantage to me is that this process is comprehensive, and with no bias – the data from the Matches is treated evenly.

Post Script: By it’s nature genealogy is an ego-centric hobby. We tend to focus on ourselves as the center of the universe. Or, if we are professionals, we treat the Client as the center of the universe. Everything revolves around our Ancestors and what we can find out about them. But each of us is a small part of the human race, and our Matches – our cousins – are part of this larger picture. They fit in, too. They are an interlocking part of the whole jigsaw puzzle, and in some (many?) cases, some of them know more than I do . The process above draws on the data they have provided. Often, they have clues to the solutions we seek. Often, they know what’s on the other side of our brick walls.

Edit 6/22/20: I’ve been asked to add a photo of my spreadsheet. Here it is – showing the top two surnames.

Spreadsheet of Cluster Common Ancestors

The 3rd column is Match Names and it has been narrowed for Match privacy. When I started, I had columns for Company and Where (the name of the Cluster run – 20cMCL63: Cluster 63 of the Shared Match run using a 20cM threshold), but it turns out this is a Quick and Dirty spreadsheet, and I didn’t need those columns. The objective is to get started on a Quick and Dirty Tree, and work from there. As soon as I saw the last line – a CRAFT married to an ADAMS, I started the Q&D Tree and found the five Matches who all tied together. Since then, I’ve used the previous blogpost on Searching and have found over a dozen more Matches who descend from this same line. All of the Cluster Matches were over 20cM. However, now knowing what I’m looking for, the Search process let me drop below 20cM and find many more – and most of them have above-20cM Shared Matches from the same Cluster. This is added evidence that I tie into this line some how.

[19H] Segment-ology: Let the Matches Tell Us the Cluster Common Ancestor by Jim Bartlett 20200620

Using a Group Common Ancestor

A Triangulation (and grouping) Concept

We have spent a lot of time and effort to describe *how* to group our Matches: segment Triangulation, DNA Painting, Shared Match Clustering. Each of these processes results in a group of Matches that should have a Common Ancestor (CA). This is an important concept.

But the main thing is to *use* this concept – to use the information found in these groups. If a group is formed around a CA, then all of the Matches in the group should share a CA. Once a CA is found, each Match in the group should also have that group CA, or be a closer cousin with an MRCA that descends from the group CA, or have a more distant MRCA which is ancestral to the group CA. In other words, all the Matches in a group should have the same distant CA.

So… if we find a CA for a group, the other Matches in the group should have the same CA line. This is a powerful focus – let’s *use* it. We should be able to look at other Matches in the group (who have Trees) and find that CA – either directly through a search, or indirectly by building out their Tree.

I illustrated this in Case 3 of Chapter 1 (Lessons Learned from Triangulating a Genome) of “Advanced Genetic Genealogy: Techniques and Case Studies” – here or here. This was all about one of my TGs which I call [04P36]. At Ancestry, I found a few cousins (who had uploaded to GEDmatch) in that TG who  shared my HIGGINBOTHAM ancestry. Armed with that hint, I searched for HIGGINBOTHAMs in other Matches (in that TG) who had trees. I also contacted Matches from FTDNA, 23andMe and MyHeritage – and several replied that they had the same HIGGINBOTHAM Ancestry. In the end I found 14 different Matches ranging from 4C to 8C on this HIGGINBOTHAM line in TG [04P36].

Because TG [04P36] came down a line of descent with the HIGGINBOTHAM surname in 5 generations, this case was an easier example – searching for one distinct surname. If a group represents a CA with a male-female zig-zag line of descent to me, it will be harder – the surname will change often. However, each line of descent (from a given Ancestor) is fixed – and we may find Match cousins with MRCAs of different surnames, but they will all be on the same ancestral line. This is akin to “Genealogy Triangulation” – getting an alignment of multiple cousins on one line.

Finding one Match with a CA in a group is not the end of the story – it’s a clue to the beginning of more research. If we find a CA for a group, but no other Match seems to have that CA, maybe we need to look for a different CA. The “correct” CA for each group should lead to Genealogy Triangulation – agreement by other Matches on the same ancestral line. If you find a CA in a group, *use* it to find more Matches on that same line. Seek CA agreement among Matches in each group.


[08D] Segment-ology: Using a Group Common Ancestor Concept by Jim Bartlett 20200620

Using Ethnicity to Identify a Cluster

A Segmentology TIDBIT

My Ancestor 14M was John William CAMPBELL, born 1856 NY; died 1916 WV. His parents were Samuel CAMPBELL and Ann CLARK who were married 1851 in Scotland and immigrated to the US in 1853. This 1/8 of my ancestry is the only known part to come from Scotland. Several cousins have done Y-DNA testing and the CAMPELL line is the Argyll CAMPBELLs.

I have over 125,000 Matches at AncestryDNA. I have identified Common Ancestors with over 4,500 Matches – only 5 of them are on my CAMPBELL line. About 12.5% of my DNA is from my CAMPBELL line, and, all other things being equal, about 12.5% of my Matches should come from my CAMPBELL line.  But all things are not equal – this CAMPBELL line is relatively small, and there are no known Ancestors before 1850, and there are no known links to any Ancestors in Scotland.

This doesn’t mean that none of my other Matches are cousins from this CAMPBELL line. However, it does result in me not being able to find any more links. I have tens of thousands of Matches with no Trees; I’ve even found some with a CAMPBELL surname – but no way to determine if I am related to them (other than the few who have matching Y-DNA at FamilyTreeDNA).

So, I drop back and relook at the big picture: exactly 1/8 of my Ancestry came from Scotland (well, maybe not going way back, but probably within a genealogy timeframe); roughly 1/8 of my DNA came from/through Scotland; and if not 1/8, perhaps 10,000 of my Matches should be on this part of my Ancestry– certainly more than the five close cousins I already knew about.

I decided to turn this lemon into lemonade. The lemon is recent Scottish immigrant ancestor – the lemonade is Scotland ethnicity. If this is the only part of ancestry from Scotland, maybe I could use that information. When I Cluster my AncestryDNA Matches at the 20cM Threshold (the lowest cM amount with Shared Matches to each other) I get about 160 Clusters. 1/8 of those is 20 Clusters – a manageable number. So when I see some solid looking Clusters without any hints of other ancestry, maybe they are from my Scotland line.

Here is one such Cluster. I clicked on the link for each Match and checked their ethnicity:

Every Match in this Cluster has 14% to 62% Scotland ethnicity. A few scattered Matches with Scotland ethnicity might be expected randomly, but for all of them to have significant amounts of Scotland ethnicity is a strong clue.

I think I can safely assume this CL149/14/[Scotland…] Cluster represents my Ancestor, John CAMPBELL – Ahnentafel 14M. If I knew the DNA segment, I could Paint this Cluster. I have several others that also show a pretty clear Cluster “picture”. Next I’ll be looking a some other Clusters which may even have a ThruLines Common Ancestor in them, but also have a lot of Scotland ethnicity – the ThruLines CA may be the outlier… With only one ThruLines CA I don’t have a high confidence that it’s right. But with high concordance of Scottish ethnicity, that’s a strong clue the Cluster is on my CAMPBELL line.

The next step is studying any Trees in these Scotland Clusters to see if those Matches have some Common Ancestors among themselves… That will be the sweetest lemonade of all.


[22AU] Segment-ology: Using Ethnicity to Identify a Cluster TIDBIT by Jim Bartlett 20200612

Clusters at Brick Walls

A Segmentology TIDBIT

Finding Common Ancestors with Matches in a Cluster sometimes “stops” at a specific generation – for example at the 3xGreat grandparent [4C] level. In other words, I’ve found cousins up to that generation, but not beyond. When one of these 3xGreat grandparents is a Brick Wall (or an “iffy” Ancestor), that’s probably the reason. The Cluster really goes back farther, but I don’t recognize any Common Ancestor further back.

It’s time to research and take notes.

I see three courses of action:

  1. If a surname is known or suspected, look in the Cluster for Matches with Trees and search them for that surname. Often, when I find one, I can build the Match’s ancestry out from there – looking for a link to my line.
  2. If a surname is unknown, jot down each Match’s surnames and try to find a Common Ancestor among them. Then I build the family around that Ancestor – looking for a link to my line.
  3. Alternatively, look for a common place and time approximately where the Cluster stops. Noodle around for any likely links. Check other Matches in the Cluster for those same links.

I use the Shared Clustering program which shows me the Matches for each Cluster, Common Ancestors from ThruLines, the number of people in their Tree, my Notes, and a hyperlink back to their AncestryDNA Profile. For each Cluster it’s easy to see potential CAs, then click on Match links, and see the surnames in common or call up their Tree for a more in depth review. It goes pretty quickly.

The result of these courses of action have ranged from easy “low hanging fruit” to “Mission Impossible”. In other words – sometimes it works, sometimes it doesn’t. I try these alternatives because they work in enough cases to encourage me to try more. I hope they will help you.


[22AT] Segment-ology: Clusters at Brick Walls TIDBIT by Jim Bartlett 20200507

Are Overlapping Segments Triangulated?

This question comes up often. The answer is: we cannot tell from just the fact that two shared DNA segments overlap in a chromosome browser.  Here is the picture we see:

11D Figure 1 Browser

In this picture, you are normally A and you have two Matches, B and C, which show as overlapping on Chromosome 6. Because they overlap, is this Triangulation? Do A, B and C shared the same Common Ancestor? We cannot tell from this picture.

Assuming the shared DNA segments are Identical By Descent (IBD) – generally true for all such shared segments over 15cM – there are two possibilities:

  1. They are on different Chromosome 06’s in A. Remember we have two of each Chromosome – one from our mother and one from our father.


11D Figure 2a Two Chr

In this case, we are (somehow) looking at just A’s two Chromosome 06’s and showing where the shared DNA segments are on A’s DNA. It looks just like the picture we saw in the browser – two overlapping DNA segments. But in this case A & B are sharing on A’s maternal Chromosome 06; and A & C are sharing on A’s paternal Chromosome 06. These two Chromosome 06’s are physically separate (think of two strands of spaghetti). Because A & B have a shared DNA segment, they have a Common Ancestor (CA) who passed that DNA down to them. Because we know in this example that it’s on the maternal Chromosome (the one from A’s mother), we know the CA is on A’s maternal side. Similarly, we know the CA with C is on A’s paternal side. Yes, there is a very unlikely chance that these two CA’s could be the same person, and the DNA segment came down two very different paths to A’s mother and father. I’ll not be sarcastic here – you can decide for yourself if you think that is possible (or what the probability is) in your case.* In general, in genetic genealogy, we conclude that B & C are probably not related to each other – at least not on this segment.

  1. Alternatively, the two shared segments are on the same Chromosome 06 in A – let’s say, for example, they are both on the maternal side (imagine the two bars below on one Chromosome).


11D Figure 3a One Chr

In this case, we are (somehow) looking at just A’s one maternal Chromosome 06, and showing where the shared DNA segments are. Again, it looks just like the picture we saw in the browser – two overlapping DNA segments. But in this case A & B and A & C are sharing on A’s maternal Chromosome 06 (they are both on the same strand of spaghetti). From the beginning of the A & C shared segment to the end of the A & B shared segment, we are looking at the exact same place on A’s Chromosome 06. For there to be a match, all the tested markers (SNPs) are the same. In general, in genetic genealogy, we take this to mean that this DNA came from the same Common Ancestor. It came from that CA down to A and to B and to C. Because both B and C share this same segment of DNA found on one Chromosome 06 in A, both and B and C should themselves show up as a Match to each other. After all they have the same DNA over this area of their own Chromosome 06.

You may have noticed that I stated each explanation of the two possibilities with: “In this case, we are (somehow) looking at…” Well we can’t just look at just one chromosome in a browser and compare it to someone else’s DNA. We don’t have that technology for genealogy DNA testing. But if we could, that is what we would see (probably without the color coding). But we cannot! We can only visualize it. So what can we do?

We use reverse logic. In the first possibility, we noted that B & C wouldn’t match each other; and in the second possibility, we noted that B & C should match each other. That is information we often can determine (at 23andMe, MyHeritage and GEDmatch – and round-aboutly at FTDNA). So, we say that if A matches B, and A matches C on the same/overlapping DNA segment, AND B matches C there too, it indicates the second possibility above – the three of them share the same Common Ancestor. This case of A=B=C=A is called segment Triangulation, and the three Matches are in a Triangulated Group [TG]. There is more about Triangulation here.

In my case, I have close to 20,000 Match/segments – each shared DNA segment is in one of 372 TGs which cover all of my DNA. In other words, these 372 TGs form a segment map of my 45 Chromosomes. The objective now is to determine the Ancestors who passed these TGs down to my parents and then to me.

*If you want to check to see if you have the same segment from your mother and your father, upload your DNA to and use the “Are Your Parents Related” program. It will show you any such segments, which is good information to have in any case.


[11D] Segment-ology: Are Overlapping Segments Triangulated? by Jim Bartlett 20200414

Download Your AncestryDNA Matches in 10 Minutes!

A Segmentology TIDBIT


UPDATE: AncestryDNA has issued a cease and desist order, and this process is no longer available to download your Matches. Sorry about that.

That is download: all your Matches, a hyperlink [to their Page as a Match to you], Shared cM, Shared Segments, Tree Type, Tree Size, Common Ancestors [per ThruLines], a tic for each Dot and Star, and your Notes! This fast download does NOT include your Shared Matches, which may take days to download.

Here’s the process:

  1. Before running this program, I set up a separate folder with todays date [e.g. 20200409] for each download; the Shared Clustering program will give you a chance to select this folder and to rename the download file.
  2. Download the Shared Clustering program. See my review of this program here. The link to upload this program is:
  3. Click on Download TAB
  4. Enter your Ancestry user name and password [stored on your PC only]
  5. Click on Sign In
  6. Select your Test (if you have access to more than one)
  7. Click the button for Fast but incomplete
  8. Open Advanced options
  9. Lowest centimorgans to retrieve: 6 [this includes all of your Matches]
  10. Lowest centimorgans of shared matches: 4000 [this means don’t download any Shared Matches]
  11. Click on: Get DNA Matches


Here’s a picture of the message when the download is complete:

So 125,000+ Matches in 6 minutes – your results may vary.

After the download, Export the downloaded txt file to Excel. Click on the Export TAB, and follow the prompts to create an Excel file – takes about 4 min.

You can then use/manipulate the Excel file. You can sort on any field, and you can edit any Notes and then Upload those revisions back to AncestryDNA. I use this as an opportunity to do a Quality check of my Notes, and to insure I have a Note for each Match with a ThruLines Common Ancestor. I find it’s much easier to edit Notes in the spreadsheet, than to jump around to each Match at AncestryDNA. NB: Don’t edit Notes in AncestryDNA when you are also editing Notes in the spreadsheet. If you do any edits in AncestryDNA, you need to do a new Download (it only takes 10 minutes!)


[22AS] Segment-ology: Download Your AncestryDNA Matches in 10 Minutes!

TIDBIT by Jim Bartlett 20200409 EDITED 20200808

AncestryDNA ThruLines Missing Out

A Segment-ology TIDBIT

ThruLines is based on genealogy – it finds Common Ancestors based on your Tree and the Trees of others. However, it only reports Common Ancestors with your DNA Matches. So, in a sense it has a DNA component. But the connections TL finds are not based on shared DNA cMs, Chromosome location, segment Triangulation, Clustering or Shared Matching – it is based only on connections found through Trees (only on genealogy). And ThruLines only reports Common Ancestors with your DNA Matches.

This is a two edge sword:

  1. If you only want to work with DNA Matches, it’s a good thing.
  2. However, if you are a genealogist looking for cousins who might share records, pictures, stories, analysis, new branches, etc., it leaves something out. Remember that roughly half of our 4th cousins (4C) don’t share DNA with us, and roughly 90% of our true 5C don’t share DNA with us, and the vast majority of our more distant true cousins don’t share any DNA with us. This means that, although a program like ThruLines could find those non-DNA-sharing cousins for us, it doesn’t. Think of all that we are missing – think of all the lost opportunities.

Well… looking back on the #1 cutting edge of the sword – I’ve got to be a happy camper. I’m finding more ThruLines Matches than I can keep up with. By adding children and grandchildren of my Ancestors in my Tree, ThruLines is finding more Matches with Common Ancestors. And these Matches and their Trees are reinforcing my Tree (and pointing out a few soft spots…)

Back to work… Stay safe!


[AR] Segment-ology: AncestryDNA ThruLines Missing Out – TIDBIT by Jim Bartlett 20200326