I often get questions about which matches should be used when doing the Leeds Method. For the most part, it depends on what you already know about your family and matches.
Unknown Biological Parent or Grandparent
If you are trying to identify an unknown biological parent or grandparent, you probably don’t know your 2nd and 3rd cousins. In that case, I recommend using matches who share between 90 and 400 cM of DNA with you. This is because we are hoping to find 2nd and 3rd cousins and avoid any first cousins who share two grandparents with you. And, for most people this range works.
(Read this post to understand why we want 2nd cousins but not 1st cousins.)
Known Biological Parents and Grandparents
However, if you know your biological parents and grandparents and are able to identify some of your matches, you should use those matches who share only ONE grandparent with you and avoid those who share TWO grandparents with you.
Above I’ve shared a diagram of me and my first cousin once removed (1C1R), “Dave.” We share 350 cM of DNA. Let’s look at two scenarios:
If I were creating a Leeds Method chart and he was a “key person”—that person who started a color cluster and I used his Shared Matches to create the color cluster—then the chart would be fine. He shares only one of my grandparents with me: Hazel.
If he was creating a Leeds Method chart and I was a “key person,” then that color cluster would include matches from two of his grandparents: Emil and Myrtle. Instead, he should exclude me on his initial chart.
Why avoid 1st cousins?
When using the Leeds Method, we are hoping to discover four clusters based on our four grandparent lines. First cousins, however, match us on either our dad’s or our mom’s side. If we created clusters based on them, we could potentially only get 2 clusters instead of 4.
Can I add in 4th cousins?
I suggest creating the initial chart first. But then, yes, you can add in 4th cousins. In fact, it’s encouraged!
But even after consolidating your clusters, some of you will still have more than 4 clusters. In fact, some of you will still have quite a few clusters. But, why? Well, for many of you it’s because you don’t have any—or don’t have enough—2nd cousins.
Why Second Cousins?
The Leeds Method attempts to use 2nd and 3rd cousins to sort your DNA matches into groups of people who are closely related to each other. In a best case scenario, your chart will have 4 clusters with each of your 4 clusters representing a grandparent line. But, most people need 2nd cousins to make this happen. Let’s discuss “why.”
We have 2 sets of grandparents & 4 sets of great grandparents (grandparent images attributed to vectorpouch)
We all have 4 grandparents and 8 great grandparents. Our (full) 1st cousins share a set of grandparents with us. They are either on our dad’s side or on our mom’s side.
If we sort our matches based on 1st cousins, we could get 2 groups (cousin images attributed to brgfx)
If we sort our cousins based on 1st cousins, we would potentially get two groups. One group would represent our dad’s side of the family, and the other group would represent our mom’s side of the family.
Our (full) 2nd cousins share a set of great grandparents with us. They are either on our dad’s dad’s, dad’s mom’s, mom’s dad’s, or mom’s mom’s side.
Our 2nd cousins share a set of great grandparents with us.
If we sort our cousins based on 2nd cousins, we potentially get four groups. This is because our 2nd cousins are the descendants of our grandparents’ siblings. And that is why we use 2nd cousins in the Leeds Method.
Since our cousin lists are built on shared DNA, the Leeds Method uses 3rd cousins to fill in some of those DNA gaps.
NOTE: If you know who some of your matches are, you want to skip any who share more than one grandparent with you and use any who share only one grandparent with you! (I’ll be blogging about this next.)
Example
Here’s an example of a Leeds Method chart that has 19 people sharing between 90 and 400 cM. However, instead of the hoped for 4 clusters, this chart has 8 clusters. It also has no overlap. In other words, each person sorted into only one color cluster group.
An example of a Leeds Method chart with a lot of clusters because of few or no 2nd cousins
If you look at the numbers on the left hand column, you’ll see that these numbers are on the low side of the recommended range of 400 to 90 cM. Many of these matches are likely 3rd cousins. If we don’t have 2nd cousins to “tie” our cousins together, we will get more clusters.
Next Step
No matter how many clusters you get, your next step is to figure out what each cluster means. If your biological parents and grandparents are known, you are trying to figure out which grandparent or great grandparent the group represents. If your biological parents or grandparents are unknown, you will want to work with the matches in the group and see how they connect to each other.
I hope this helps! And, as always, feel free to write and ask me your questions!
I posted earlier this week about how and why you might need to consolidate (or combine) your color clusters on your Leeds Method chart. Today, I’d like to share an example from a reader named Bruce.
Original 9 Clusters
When Bruce sent me his chart, he had sorted 50 people into 9 clusters:
Bruce’s Original Leeds Method Chart
With a lot of clusters and a lot of overlap, Bruce’s chart would be more helpful if we consolidated some of his clusters. Although not always possible, we are hoping to be able to create 4 clusters based on his 4 grandparent lines.
Rearranging the Clusters
To consolidate clusters, I first rearrange them by putting clusters with overlap next to each other as seen below:
Bruce’s Clusters Rearranged
In Bruce’s case, we have overlap with the following clusters:
Clusters C, D, & E
Clusters F, G, & H
Clusters I & J
Next we look to see if there is “heavy overlap.” In other words, do most of the people in one color cluster also belong to another color cluster? Let’s look at two examples:
Do most of the people in Cluster D (gold) also belong in Cluster C (bright red)? Yes, they do. So I would consolidate or combine these two clusters into Cluster C. We would then ask the same question about Cluster E: Do most of the people in Cluster E (red) also belong in Cluster C (bright red)? Yes, they do. So I would consolidate or combine these two clusters into Cluster C. That means that Clusters C, D, & E were combined into one Cluster: the Red Cluster (C).
Do most of the people in Cluster J (light blue) also belong in Cluster I (dark blue)? Yes, they do. So I would consolidate or combine these two clusters into Cluster I.
Consolidating Clusters
In this case, I consolidated as follows:
clusters C, D, & E into a Red Cluster
clusters F, G, & H into a Green Cluster
clusters I & J into a Blue Cluster
(Note that the Yellow Cluster, with just a single person, was left alone)
We get the following chart:
Bruce’s Leeds Method Chart after Consolidating
Now Bruce has 4 clusters, which is a “best case” scenario! These 4 clusters likely represent his 4 grandparent lines.
Bruce has been able to identify the Red and Green Clusters as belonging to his maternal grandfather and grandmother. He has a mystery on his dad’s side, so hopefully he will find the answer by researching the Blue and Yellow Clusters!
Adding Higher Matches
Let’s take this a step further and talk about the next step. The next step would be to add any higher matches. If some of these higher matches are related to you through 2 grandparent lines, they will likely match 2 Color Clusters.
Bruce’s Blue and Yellow Clusters
In Bruce’s case, he only has 1 match above 400. This match only shares 401 cM. Interestingly, the person matches both the Blue and Yellow Clusters supporting the idea that the Blue and Yellow Clusters are paternal while the Red and Green Clusters are maternal. If Bruce can figure out this person’s 4 grandparents, it might help him with his own mystery!
Any Questions?
I hope this helped as you figure out how to consolidate your own clusters. If you have any questions, please feel free to ask!
Today I want to discuss one of the most frequent questions I get: Why did I get more than 4 color clusters on my Leeds Method chart?
(I’ll address the issue of getting less than 4 clusters in a future post.)
The Simple Answer
There are basically two answers to this question.
You don’t have enough second cousins. (We will also discuss this in a future post.)
You need to do another step which is consolidating (or combining) some of your clusters.
Key Concepts
As we discuss this, let’s keep a few key concepts in mind:
The goal of the Leeds Method is to naturally sort our DNA into clusters of matches who are biologically related to each other.
We hope to get 4 clusters representing our 4 grandparent lines. However, not everyone will get 4 clusters! (In other words, your results may vary!)
Many people need to consolidate (or combine) clusters to “see” their grandparent lines.
The Leeds Method
Let’s start with a simple, fictional Leeds Method chart which created 5 clusters using these basic steps:
List all of your DNA matches between 400 and 90 cM.
Assign the color blue to your highest match, Lori, and add an asterisk to her.
Assign the blue to all of Lori’s Shared Matches: Joe, Rebecca, and Liam. (Note: A Shared Match is a person who shares DNA with both you and your match, Lori.)
Assign the color red to the highest match that doesn’t already have a color, Meredith, and add an asterisk to her.
Assign red to all of Meredith’s Shared Matches: Joe and Rebecca.
Continue steps 4 and 5 until everyone has at least one color. (Note: These steps created the Green (Lynne), Yellow (Lucy), and Purple (Mitzi) Clusters.)
Leeds Method Sample Chart
Overlap and Heavy Overlap
We’ve now completed our initial Leeds Method chart. We were hoping to see 4 clusters, although we know some people will have more or less than 4 clusters. Our chart has 5 color clusters.
But our chart shows overlap. In fact, it shows heavy overlap. So let’s define these two terms:
overlap – a person with more than one color. In this example, Joe and Rebecca were assigned both the color blue and red, so they have overlap.
heavy overlap – most of the people in one cluster are also in another cluster. In this example, 2 out of 3 of the Red people are also in the Blue Cluster. Also, 2 out of 4 of the Blue people are also in the Red Cluster.
Whenever we see heavy overlap, as in this case, my recommendation is to combine those colors into one. In this case, we would combine the Blue and Red Clusters. This would give us a total of 4 clusters.
Next, I’ll explain why I recommend consolidating clusters. This is a more advanced explanation. If you want to keep things simple, you might skip this part! But if you want to understand why these clusters probably formed then continue reading.
Seeing the Segments
As you probably know, we cannot see the segments (or pieces) of DNA we share with our matches at Ancestry. This is because Ancestry does not have a chromosome browser. But let’s pretend we can see the segments of DNA using a fictional chromosome browser. For simplicity, we will only look at the 5 people who make up the Blue and Red Clusters. (Remember, those are the two clusters that have heavy overlap between them!) And, we will pretend that all of the matches showed up on one of your chromosomes: chromosome #1.
In this pretend scenario, let’s also assume that you have identified these 5 matches and know they are all related to you through your Grandpa Fred’s part of the family.
Below are the fictional chromosome browsers for you and your 5 matches we determined were biologically related to Grandpa Fred. Each chromosome is broken into 6 segments which are numbered from 1 to 6. The grey segments are those inherited from Grandpa Fred’s part of the tree.
Fictional chromosome browser showing DNA segments inherited from Grandpa Fred
The Blue Cluster
Now let’s think about how we created our chart. When we used the Leeds Method, Lori, who inherited segments #2-5 from Grandpa Fred, started our Blue Cluster. Her Shared Match list included the following people: Joe, Rebecca, and Liam. They showed up on her Shared Match list because they share DNA with both you and Lori.
With this fictional chromosome browser, we can see that Lori shares the following DNA segments with these matches:
Joe at segment #3 & #4
Rebecca at segment #3
Liam at segment #2 & #3
Note that, although Meredith also has DNA from Grandpa Fred’s part of the family (segments #1 & #6), Meredith and Lori don’t share any DNA segments. So, Meredith would not show up as a Shared Match of Lori’s. And Meredith did not end up in the Blue Cluster.
The Red Cluster
Instead of being a part of the original Blue Cluster, Meredith—at step #4—started the Red Cluster. Using the fictional chromosome browser, we can see she matches both Joe and Rebecca at segment #6. So Meredith, Joe, and Rebecca are the Red Cluster.
Consolidating Clusters
By using this fictional chromosome browser, we can see why Lori, Joe, Rebecca, Liam, and Meredith should all be in one cluster. They all came from one part of your tree! They are all related to Grandpa Fred! They only ended up in two different clusters because Lori and Meredith didn’t happen to inherit identical segments of DNA.
In this case, we also know they all belong in one cluster because we were able to identify these 5 matches and determined they were all related through Grandpa Fred’s line.
But, even without a browser or identifying these 5 matches, we can see the heavy overlap. When you see heavy overlap, you should probably combine the clusters!
A Chart with 4 Clusters
After consolidating the Blue and Red Clusters into one cluster, the Blue Cluster, we end up with 4 clusters. Each of these 4 clusters likely represents one of your 4 grandparent lines:
Do we need a chromosome browser?
In real life, we do not need to be able to see these chromosome segments to create these clusters! Instead, this example is meant to show you why people who are related to each other—like Lori and Meredith—might end up in different clusters. This happens because they don’t share segments of DNA. However, we can still combine clusters—and thus have Lori and Meredith in the same cluster—based on heavy overlap.
Questions?
I hope this helps! Please let me know if you have any questions or comments.
My husband is blessed with probably hundreds of old family photos through one of his grandparent’s lines: his Payton family. Many of these photos are labeled. But, his mom, dad, and I worked on labeling more of these this weekend.
I was intrigued by one photo that was sent as a postcard. The picture was of an unknown mother and baby. The back was written to “Aunt Ella” and signed “Maud Vassar.”
Payton (Gilbert) Family Photo
Three other people were mentioned: Myrtle, Ben, and Leona. I had three questions:
Who were the people in the photo?
What year was the photo taken?
And who were the people mentioned in the postcard?
Aunt Ella, Ben, & Leona
A penciled label on the side helped me determine that “Aunt Ella” was Mary Ella (Gilbert) Payton, my husband’s great, great grandmother. Ben, her oldest son, was my husband’s great grandfather. Leona was Ella’s second oldest child.
Payton (Gilbert) Family Photo
Niece Maud Vassar
I originally misread the letter and thought two nieces – Maud and Myrtle – were writing their Aunt Ella. I did identify Maud. She was a daughter of Ella’s sister, Waity Belle (Gilbert) Robbins. And Maud’s married surname was Vassar.
Without information on many of Ella and Waity Belle’s nine siblings, I could not find another niece named Myrtle. I did notice that Maud had two daughters who appeared to be twins on the 1920 census; Mabel and Myrtle who were both listed as 7 years old that year.
The FamilySearch Tree
To try to determine if one of Ella’s other siblings had a daughter named Maud, I turned to the FamilySearch tree. The tree did have more information – some sourced and some not sourced – and I will have to do more research before adding these people to my tree. But, I was susprised to see that Maud’s daughters, Mabel and Myrtle, were not twins! According to the birthdates listed on this tree, Myrtle was born 19 January 1912, and Mabel was born less than a year later on 5 January 1913.
The Mother/Daughter in the Photo
Finding out that Maud’s first daughter was named Myrtle helped me to read the postcard with a different viewpoint. I had thought the letter was from Maud and Myrtle. But the letter actually starts by saying “this is me and Myrtle.” So, the mother is Maud and the baby is her daughter, Myrtle! And, since Myrtle was born in January of 1912, this photo was taken in 1912. At the time, Maud must have been pregnant with her second daughter, Mabel.
Strangely, the Vassar family lived in Washington though the postcard says it’s by the “Stanton Photo Novelty Co” of Springfield, Ohio. The family might have been on vacation when this photo was taken.
It was exciting to do the detective work to not only identify the people mentioned in the postcard, but also to identify the mother, daughter, and year of the photo!
UPDATE: My friend, Natalie, shared some information about novelty photo companies and Stanton in particular. These companies ran ads in various publications offering photograph reprints. She also sent a link to a blogpost about Stanton Photo Novelty Company on a website called Evermore.
When I need to find wills or probate records, I usually start at FamilySearch to see what is available. I go to their online catalog, enter the place name, and see what is available under the “probate records” category.
Seeking the Probate of James B. Leeds
Recently, I was seeking the probate of James B. Leeds who appeared to have died in Ripley County, Indiana, between the 1840 and 1850 censuses. The FamilySearch result page showed two items under probate records:
Probate for Nov. 1818 to Feb. 1837 – too early for James
Will records for 1839 to 1922 – a good possibility for James!
The “will records” included more than just wills! There were dozens of microfilms listed, but they fell into 3 categories:
wills
probate order books
complete probate order books
Unfortunately, these files are locked and can only be accessed from a Family History Center or a FamilySearch affiliate library.
Are these records available online?
FamilySearch Wiki
Arguably the best place to start your research in a given location is the FamilySearch Wiki. You can enter a county and state and find a lot of information about that location – including information about probate records.
The wiki page for Ripley County, Indiana, showed that Ancestry.com has a database titled Indiana Wills and Probate Records 1798-1999.
Indiana Wills and Probate on Ancestry
Heading over to Ancestry, I looked under “search” and then “card catalog.” For the title, I entered “Indiana wills and probate” then clicked on the link.
I was pleasantly surprised to see this recordset had a search box! But quickly disappointed when I searched for James Leeds…and got NOTHING!
I checked to make sure the search feature worked by searching for “James Smith” and got 161 results. I also searched for “Smith” in Ripley County to make sure that Ripley County was included and got 31 results.
So, does James Leeds not appear in this database?
Browsing the Collection
Besides the search feature, there is also a “browse” feature for this database. You can start by choosing a county, so I selected “Ripley County.” I found the same three categories that had been listed on FamilySearch:
wills
probate order books
complete probate order books
Will Book B covered the right time frame (1839-1862), so I opened that database to see if it had an index. It did, but there were no “Leeds” listed.
My next plan was to search Probate Order Books B (1837-1843), C (1843-1846), and D (1846-1849). Thankfully, Probate Order Book B included an index. And there were entries for the estate of James Leeds!
Index to Probate Order Book B, Ripley County, Indiana
Multiple pages were listed, so I looked at all of them. The case continued through 1847 into books C and D.
Ancestry (https://www.ancestry.com : accessed 25 August 2020) > Indiana, Wills and Probate Records, 1798-1999 > Ripley > Probate Order Book, Vol D, 1846–1849 > image 442, final settlement of James Leeds estate, 1847.
This file really helped me put this family together. The final settlement of the estate listed the 13 children also providing married names for the daughters! (See image above.)
This final settlement appears to be based on the selling of a piece of land to someone named “Falls.” Unfortunately, a receipt was lying over part of the document when it was imaged so parts of the page – including the buyer’s first name – were hidden.
Complete Probate (or Order) Book
Indiana also has “complete” probate or order books – something I’ve never seen. On Ancestry, they call these “Complete Order Books” from 1834 to 1848 and “Complete Probate Books” from 1848 to 1917. These books “compile every action made by the court pertaining to a certain estate.” This is a wonderful find which helps me get past the receipt that was microfilmed in the probate book!
(The quote is from the “Indiana’s Gore – Genealogy Resources” post found here. It also has a searchable index to the Ripley County records! )
Ancestry (https://www.ancestry.com : accessed 25 August 2020) > Indiana, Wills and Probate Records, 1798-1999 > Ripley > Complete Order Book, Vol C, 1846-1846 > image 313, list of James Leeds’ heirs at law, 1844.
This book also has wonderful additions not seen in the probate – including complete word-for-word descriptions of deeds that are only mentioned in the other probate books! Possibly the most important page is that final deed that gave land to someone named “Falls.” This book records the entire deed and shows that the land was sold not by Eva Leeds or the heirs of James Leeds, but by Samuel H. Spooner, an appointed commissioner, to a Michael Falls. (See image 312 of Complete Order Book, Volume C.)
Searching for Wills and Probate
If you are searching for wills and probate records, I suggest you start with the FamilySearch Wiki. Also, if you find a searchable database but can’t find your ancestor’s name, try browsing the collection! If the individual books don’t have indexes, you might have to look through the book page by page. But, in the end, it might very well be worth it!
The Leeds Method sorts your DNA matches into clusters. The members of each cluster are likely descended from a common ancestor or ancestral couple. Finding the common ancestor(s) for a cluster helps us to understand how these matches are related to each other and to us. And this method can help us to verify our ancestors or to break through brick walls.
While the Leeds Method is a powerful tool, unfortunately it cannot help everyone. Can the Leeds Method help you?
Sample Leeds Method Chart
Works Well
The Leeds Method works well in the following situations:
If you have “quite a few” 2nd and 3rd cousins
The Leeds Method is based on, and needs, 2nd and 3rd cousins. As a generalization, those are matches between 400 and 90 cM. Although I cannot give an exact number, the Leeds Method often works well if you have at least 6 to 8 matches at this level. And some of them should be in the 200 to 400 cM range.
If you do not have endogamy or pedigree collapse
The Leeds Method works well if you do not have endogamy or pedigree collapse in your tree – or if it is on only one part of your tree. (Note: I will define both terms under the section for when the Leeds Method does not work well.)
If your grandparents are not related & came from different areas
If your grandparents are not related to each other, the Leeds Method works well. It also helps if they came from very different areas so there’s little chance that they might have a surprise connection or that a match might be related to two of your grandparents.
Doesn’t Work Well
The Leeds Method, unfortunately, does not work well in the following situations:
You have endogamy or pedigree collapse in your tree
Endogamy is the practice of a specific group of people marrying within their group for generations. Pedigree collapse is the occasional occurrence of cousins marrying cousins which used to be a fairly common practice. Both of these situations result in your matches being related to each other in multiple ways. And that causes the clusters to merge together instead of creating separate clusters.
However, if you have endogamy or pedigree collapse in just part of your family tree, you can still use the Leeds Method to separate out other parts of your tree.
You have few or no 2nd-3rd cousins
The Leeds Method is based on 2nd and 3rd cousins. If you don’t have any of these matches – or very few – the Leeds Method will not work as intended. However, you can still use it to create clusters with whatever matches you DO have!
Sadly, Ancestry.com has announced they will soon be removing all our DNA matches who share less than 8 cM of DNA with us.
We are told that about half of our 7 cM matches are false. But, that also means that about half of them are true!
And, though some of these matches will be distant relatives, others are closer and easier to work with. Sometimes, these very small matches provide valuable clues that lead to wonderful discoveries. They can even help us break through our brick walls.
My friend, John, was working with his paternal matches last weekend and found a 7 cM match – through ThruLines – that had a well-documented tree. This tree included sources that helped him trace his line back to Italy and extend his tree another generation!
Finding His Family’s Village in Italy
Finding our immigrant ancestors’ village of origin can be difficult.
John knew that his great grandparents, Vincenzo Beatrice and Angela Valente, were both born in Italy. Growing up in different towns in central Italy, they met and were married in the U.S.
“Massachusetts, Marriage Records, 1840-1915,” Ancestry (https://www.ancestry.com : accessed 24 July 2020) > _Up Through 1910 > 1903 > image 550, no. 40, Vincenzo Beatrice and Angela Valente.
Their 1903 Massachusetts marriage record listed both of their parents. Angela’s parents were Vincenzo Valente & Carmina Rossi.
Before last weekend, John had never seen an Italian record for this family. But, while working with some of his very small matches who appeared in his ThruLines, he found a match’s tree which identified the Italian town for this family. Even better, it included documents from the Italian Stato Civile – the Civil registration of births, marriages, and deaths in Italy.
Using FamilySearch, he found the birth record for his great grandmother, Angela Valente. And, he found the birth and marriage records for his 2x and 3x great grandparents. He also found the names of his 4x great grandparents!
“Nati [births], v. 94, parte [part] 3, 1850-1855,” in “Italia, Frosinone, Atina. Stato Civile [civil records] : Comune [municipality], 1809-1929,” FamilySearch (https://www.familysearch.org : accessed 24 July 2020), FHL film #5715449, image 24, p. 83, birth record, Vincenzo Valente (1854). The note in the red box says “noniugato con Rossi Carmina su Pietro in Atina 17 5 1875” meaning “married to Carmina Rossi of Pietro in Atina 17 May 1875.”
Excitingly, when a person was born and married in the same town, the clerk made a notation of the marriage in the margin of the birth record. So, John was able to easily piece his family together!
Before finding this well-documented tree through a very small, 7 cM match, John only knew for certain the names of his great, great grandparents based on U.S. records. He was uncertain of their town of origin. But now he has wonderful records tracing this family line back to his 4x great grandparents.
Connections & Discoveries
The fact that John made this great connection doesn’t prove that those 7 cM of DNA are real or that this match was real. However, the connection was real and John made incredible discoveries.
Without this match, John hopefully would have eventually found these records. But, he found them now – and a new cousin connection – because of a very small match that exists today. But very small matches like these will soon be deleted by Ancestry.
If you want to learn more about how you can save your matches, read my post here.
Elizabeth Shown Mills shared this post on Facebook stating that “Culling Ancestry’s gargantuan DNA database certainly will increase its efficiency—but the cost is one our field cannot afford.” She went on to say, “The stance that ‘small’ segments are too ancient and too problematic is a short-sighted stance in a field that is rapidly developing new methodology, new strategies, and new tools.”
In response, my friend and colleague, Franklin Smith, who is an African American, shared a heartfelt response about how the changes Ancestry is enacting will negatively affect those researching their enslaved ancestors. I asked him if he would write a guest post on my blog, and he graciously agreed.
Franklin’s great aunt, Sylvia (Bowens) Woods (b 1860 in MS) holding little Henry Campbell who is black (mulatto). Her parents, Franklin’s great grandparents, were both born in Virginia and sold south. Her brother, Franklin’s grandfather, was born free in 1873. Photo in collection of Franklin Smith. Used with permission.
Researching Enslaved Ancestors
My name is Franklin Carter Smith. I’m African American and have been researching my African American ancestry for nearly forty years. I specialize in slavery-era research and am the co-author with Emily Croom of A Genealogists Guide to Discovering Your African American Ancestors.
My mission from the day I identified my first enslaved ancestor was to tell the stories of their lives while enslaved. The first thirty years were spent trying to break through slavery’s 1865 brick wall. Persistence and diligence led to the identity of most of my ancestors’ enslavers, an accomplishment of which I’m very proud. They were no longer invisible. However, like other descendants of the Deep South Mississippi enslaved people, my oldest post-Civil War ancestors were born in the upper south, from Virginia to Georgia, and sold or moved south. The chance of tracking them back to their upper south origins was extremely unlikely if sold south as I believe mine were. After exhausting all the available paper resources I needed a new approach.
Using DNA
Reluctantly, I turned to DNA. I don’t have a strong science background and was admittedly intimidated. Surprisingly, it was a turning point. I saw the potential of DNA in expanding my slavery era research. After getting up to pace on a basic understanding of genetic genealogy, I immediately recognized that African Americans face a genetic brick wall in addition to their genealogical brick wall. I joined the right DNA Facebook groups hoping I could get guidance but quickly learned few understood nor was there much discussion of my unique challenges.
When I tested, Ancestry was the company of choice because most African Americans were testing there and more testers had test-connected trees. I reviewed my closer matches and realized many of my 4th cousins and closer descended from my known post-Civil War ancestors. The farther down the list I moved, it became apparent they were not matching any of my known DNA cousins. This is where slavery’s genetic brick wall began for me. Few, if any, surnames and locations in their trees matched my known ancestors. Most were from the Upper South or other states where I had no known family. Identifying the connections between those matches was my only recourse, I hoped, that might lead to a connection to my family. Rarely did that happen.
Franklin’s great, great grandparents, Henry & Angeline Dotson, who were born enslaved in 1850 and 1849, respectively, in Mississippi. Henry’s mother and Angeline’s parents were born in Virginia suggesting they were sold south. Henry’s father was his slaveholder. Photo in collection of Franklin Smith. Used with permission.
DNA Third-Party Tools
I hoped Ancestry would step up and introduce new DNA tools that would help me dig deeper into my DNA matches. Unfortunately, they did not. Instead, third parties stepped up and filled the gap by creating some amazing tools. I was extremely excited when Dana Leeds introduced her color code clustering concept. I saw the immediate benefits for African Americans and told her it would be extremely beneficial for the African American community. When Dana’s color clustering concept was automated it was a game-changer. I could finally see how the lower to lowest 7cM matches were clustering to known ancestors and to each other. This not only created a new avenue for research but also extended my ancestral lines and locations back several generations although I would unlikely ever know exactly how. Although I may never be able to identify a most recent common ancestor, I could not only hypothesize they were sold or removed from a state but from a specific county in that State or had family sold or moved to that state and county as well as the families they were related to. I reached out to many of my new cousins and felt I had brought my family together though I wasn’t sure how we were connected. I know only that our ancestors’ separation was not by choice but by force. It’s a welcomed narrative I did not have adding to the history surrounding their enslavement.
Ancestry’s Cease and Desist Letters
I was highly frustrated when Ancestry issued cease and desist letters to the clustering tool agents and DNAGedcom. Their subsequent announcement to delete and no longer post matches of less than 8 cM turned frustration into some anger. Because fewer African Americans have taken DNA tests, more at Ancestry than at any other provider, each morning I’d go “DNA diving” into my newest DNA matches looking for any match that might provide some additional clues. Not only do we have fewer matches but up to a fourth of those matches are white. Though most were not useful there were some significant finds. Ancestry’s limit on shared matching to 20 cM and higher never identified these potential gems. The loss of both has been extremely devastating to my research. Loss of the clustering tools will cause significant challenges in moving forward. I relied on these tools to bring in the lower matches that I missed.
I always reluctantly suggested other African Americans test with Ancestry because of the numbers advantage. I never felt Ancestry would create truly useful tools on their site. However, I assured folks there were good 3rd party tools useable with Ancestry that would fill the void. I followed up with presentations on how to use those tools. Now that these tools are no longer an option, I don’t know how to guide other African Americans through this maze when I don’t see a way out myself.
The African American Minority
I didn’t know how to channel my frustration or if it would make a difference. I’m in the minority and fully understand that the majority might not need these tools as badly as I did. When I saw Roberta Estes’s post on how Ancestry’s changes impact African American researchers, I knew it was time to speak out. She hit all the salient points on how Ancestry has failed to recognize the unique challenges African Americans encounter or have any useful tools that assist them in their genetic research. Consider ThruLines, for example, which cannot include enslaved ancestors whom most African American researchers have not and cannot identify. The ethnic communities suggest that I’m matching other African Americans with connections from mostly the Upper South. Something that I expected since most post Civil War Freedmen show upper south birthplaces for themselves or their parents.
I’m very appreciative to Dana for listening to and understanding my concerns and frustrations. I am aware that Ancestry’s changes have adversely impacted all researchers, but as is true with any adverse change that takes place in our society on whatever level, African Americans are likely to be more negatively impacted. Ancestry issued a statement in support of Black Lives Matter. I hope they appreciate this not only applies to what happens today but to the history that led us to where we are today.
Earlier this week, Ancestry.com announced on a conference call that they were making several big changes in regards to DNA matches. I was not on that call, but I read about the changes on Debbie Kennett’sCruwys news website. And, last night I saw an announcement on my own Ancestry account.
These changes will be taking place starting “in the beginning of August,” so you don’t have much time to save matches…if you want to save any!
The Changes
Screenshot of Ancestry Updates headerScreenshot of Ancestry updates
According to the updates, the new changes will affect the following:
More Accurate Number of Shared Segments
This is an update with Ancestry.com’s algorithm and, while you’ll still see the same total amount of shared DNA between you and your matches, you might see the number of segments decrease. This will apparently be more accurate.
See the Length of Your Longest Shared Segment
As another result of the updated algorithm, you will now be able to see “the length of your longest shared segment” between you and your matches.
Distant DNA Matches must be 8 cm or higher
This last change is one that has many people concerned. Ancestry is basically removing our matches who share less than 8 cM of DNA with us. Since the numbers they use are rounded, you will actually lose a lot of your matches who appear to share 8 cM of DNA with you. (For example, if you share 7.7 cM with a match, that would show up as 8…but it is actually less than 8 cM, so it should disappear.)
While many of these low cM matches are “false” matches, many of these matches are also real matches. And, we hate to lose them.
(NOTE: Since these low matches have now been purged from AncestryDNA, I have deleted the remainder of this post explaining how to save your matches.)
