In early 2018 we made a series of posts on how to use the multiple “Shared Matches” in AncestryDNA to narrow down the DNA line that connects you to them. The challenge was that often they have no trees, or small trees that don’t come anywhere close to matching your (much more complete!) tree.
This strategy was a way to use mirror trees to match them to themselves, which should indicate a Most Recent Common Ancestor for them, and in all likelihood to be your MCRA as well. For this series we broke down a large set of matches (5000+) to Felice’s mother, to try and establish her first DNA link outside of the immediate family.
There were all of the challenges we all face with African American genealogy (fewer family histories to draw off of, smaller trees, difficulty with 3x/4xGGP’s due to the “1870 Wall”, etc.), and in this series we found the MCRA…but we failed to find the link between them and our family. However, about a year later we broke through that wall, and we’ll be following up on that shortly. In the meantime, here’s the complete series in one page:
(Note: As always, we receive no financial benefit or consideration for any product or service we review/recommend/discuss here. Everything we discuss is our opinion alone, and we talk about it because we use it.)
When we initially started this blog, one of the first topics we covered was our standard genealogy toolkit (How to: Getting started researching your family tree) that included everything we though people would need to successfully start getting serious with this hobby, and ease folks into more advanced work. Our suggestions included Tony Burrough’s Black Roots as well Elizabeth Shown Mills’ Evidence Explained, and now Kenyatta D. Berry’s The Family Tree Toolkit is a strong addition to that list. In addition to being an essential resource, it’s a wonderful read.
The Family Tree Toolkit finds that balance of storytelling, emotional connection, and practical research examples in a way we can only envy.
From a practical standpoint, her detailed list of research resources (often state-by-state) is pretty consistently spot on for a deep dive into each subject. It’s so complete, and as hobbyists who have spent nearly 8 years doing this work, we found so many additional resources it took much longer than it should have to finish the book. We’d swear that when we read the next section, we WOULDN’T dive into one of the suggested sources for that section. We’d just make notes and come back. It never worked, and we’d spend the next 2-3 days checking out new sources! If we had this book 8 years ago, and we took the time to plan our research back then, we would be SO much further on this journey. We found a lot just doing searches and lucking into things, but if we targeted the correct sources from the beginning, it would have been so much more effective, and we’re now consulting The Family Tree Toolkit as we continue our research.
The risk with these printed texts that catalog research sources is that they will grow stale with time, and the book loses it’s value, but each of the resources here seem to have been picked to be resistant to aging. Sites like familysearch.org will be around as long as the LDS church is around (essentially, forever), and other sites tend to be big, well funded, and the collections listed are more likely to grow over time. It’s a better bet than not that the book will be an essential reference guide well into the time Ms. Berry issues her first revision.
But another reason to not focus on the nature of reference aging is that the personal journey stories and examples of Ms. Berry’s work would have made this an essential read on their own. The Family Tree Toolkit finds that balance of storytelling, emotional connection, and practical research examples in a way we can only envy. Not that our passion is ever waning, but there is a thread of deep truth that runs through her stores that not only reminds us why we’re doing this work, it re-inspired us to make the effort to make physical connections to the data we’re gathering.
For example, take this passage where she talks about her first trip to an ancestral home in Madison County, Virginia:
“As I explored the grounds, I looked out to the neighboring property and realized that I was walking in the footsteps of my ancestors. More than 130 years ago, they had stood where I was standing, and as I closed my eyes, I could almost hear their voices in the distance.”
That was a moving section that stuck with me for days…the profound nature of smelling the air your ancestors smelled, felt the same earth together under our feet as they did, had our heart filled with the same joy theirs must have looking at the same view we’re seeing. About a week later as we drove through my paternal ancestral home of Antigo, Wisconsin and passed my Great Grandfather’s E. A. Morse’s office….driving up Superior Street and coming to the corner of First Avenue, where he would have walked 1000’s of times on his way home, passing the same houses that still stand, the old service station that is right where its always been, up to their house which I still remember fondly, there’s a deep feeling of connection and home I shared with someone I only know from photographs, documents, and family stories. And I immediately was thinking of passages from Ms. Berry’s book.
Beyond that, thinking of my wife who is also descended from enslaved Africans, I understood the impact the lack of that connection she must feel. How part of this work, for her, is to find that natural connection to history and family. Seeking that profound moment she described has literally refocused our efforts to prove those links, and then stand on the same ground my wife’s family stood on.
Kenyatta D. Berry’s combination of a great compilation of research sources and deep, moving personal storytelling, makes The Family Tree Toolkit an essential part of our work, and our library.
In this installment we’re going to walk through a key tool to help narrow down where to research when you have AncestryDNA tests that match your family, but despite your research you’re not sure where they match. DNA Painter has a great tool called What are The Odds that gives us the probability of where these unmatched lines link up with our own.
We’re using a real set of unknown matches for this example. Emma Kupps (1879-1953) is a one of our favorite ancestors. She was born and raised the various logging communities that sprang up in North Central Wisconsin in the late 1800’s, but her family settled in Antigo where she graduated from Antigo High School. Within a few years she would married a logger Daniel Leonard (1868-1924), who would soon become Antigo’s Fire Chief, and years later be elected Sheriff of Langlade Coounty, Wisconsin. During his term Dan became ill with cancer, and succumbed with a significant portion of this term remaining. The governor of Wisconsin appointed Emma to the position of Sheriff to complete her late husband’s term, and she became the first woman in Wisconsin to hold the office. (Langlade Co. Historical Society)
DNA Painter has greatly narrowed down where we’re targeting our on-going research to finally break down this brick wall.
But, to family historians, she’s also near the end of a line that is a classic brick wall. Her father died young, and there’s nothing but a couple of records that indicate only the names of his parents. Plus, they are the only lines in our family that come from Bohemia, so it has the combined brick walls of classic genealogy and DNA results.
We’ve identified a group of AncestryDNA matches that have strong Bohemian roots and match descendants of Emma. We used Michael’s Great Uncle as our target DNA match, since he’s the oldest generation tested on that line, and we built a master tree that links as many of the unknown DNA matches as we could. We ended up with 8 AncestryDNA matches that we could link together in a cluster.
The cluster all share Jacob Haasl and Dorothy (Johannek) Haasl as their MCRA, but we haven’t been able to build a link between Great Uncle Leonard and the Haasl’s. So, we’re going to turn to DNApainter’s “What are the Odds” tool, to help identify where we’re most likely linked to the cluster.
When you open “What Are the Odds?”, it will present a box for the most recent common ancestors (MCRA). The options are to “Edit Names”, “Add Child”, or “Add Parent”. In this case, we’re going to edit the name, and add the cluster’s MCRA, Joseph and Dorothea Haasl. When we enter that information, we’re presented with the same 3 choices, but this time we’re going to start building a line to one of the DNA matches but selecting “Add Child” and entering the name of the child that makes up the first step to our DNA match. At first we were surprised how quickly we built out a tree, but it’s because we’re not entering all the data we’d need for a regular tree, just the names!
When we reached a DNA match we entered the cM value that matches our known DNA test. We repeated this step for as many matches as we’ve identified. This works well with a single match, but better with more. In our case we identified 8 matches, so we’re built them all out. Now we’ll really see the power of this tool.
Now that we’ve entered what’s known, it’s time to start mapping out our guesses. In fact, the entire purpose of this tool is to compare the likelihood of at least 2 hypotheses matching the entered cM, and from those likelihoods we can focus on where it’s most likely we all share a most MCRA.
The most likely connection for Jacob and Mary Keips’ line is her parents. We don’t know her maiden name, or birth date, but if we guess that she was born in 1820-1825 it’s reasonable to guess she is a sibling of either Jacob Haasl or Dorothy (Johannek) Haasl, so let’s build that out as option 1. We’ll add an “Unknown 3xGGP” to Joseph and Dorothy, and add a child called Jacob/Mary (because it could be either!). From there we’ll build down to the Great Uncle that is the known DNA match, and select “Use as Hypothesis”.
It shows us a probability of “1” because DNA painter doesn’t show you raw percentages, it shows you comparative probability of one match vs. another. For example, if you enter two hypotheses and one returns “1” and the other returns “2”, we’ll know the second one is twice as likely as the first. In this case, we have no other hypotheses entered, so it shows just a 1.
Given the cM match, it’s most likely that we match the cluster with Great Uncle Leonard’s 3x to 5x GGP’s, so we built out the same line as above, but this time with one more unknown ancestor above Jacob/Dorothy Keips, which would then make Uncle’s MCRA a 4xGGP.
When we built that out, and selected the second “Great Uncle Leonard” as a hypothetical, it soared to a whopping score of “1174” vs. the first “Great Uncle Leonard!! Given that we have 1174 for one possible link and 1 for the other, DNA painter just told us that while not impossible, we’re looking for a 4xGGP as our MCRA, not 3xGGP. Not great news, since now we have to go at least two more generations back, and to build this match back further we’re going to have to dig deep into 18th Century European genealogical records. That’s not our strong suit. But, at least now we have a clear picture of where we’re looking to link these groups.
Since the range of likely Great Grandparents is 3x-5x, we then built this hypothetical out to our match’s 5xGGP, and we see the same score of 1174 from a hypothetical 5xGGP. That means it’s equally likely that our link to this cluster of match is through our Great Uncle Leonard’s 4xGGP or this 5xGGP, but it’s almost certainly NOT through his 3xGGP.
While in some ways this is disappointing, and we’d hoped to come through with a match, this is actually a huge piece of this brickwall puzzle. When we started the work on this DNA cluster we knew that John Keips/Kupps had migrated from Bohemia and, at the time of his death, his wife thought his father was Jacob D. Kupps when she filled out her husband’s death certificate. From their marriage certificate we knew John’s mother, and Jacob’s wife, was Mary. We also knew we had a large cluster of DNA matches who came from the area of Bohemia.
Just by going through that cluster, building out a central tree that links them all, we found a great lead that likely shows John’s arrival information, along with approximate birth years for Jacob, Mary, and John…as well as John’s previously unknown siblings who seem to have a long history together in the US, and left many records. That means instead of having exhausted all the on-site research we could do on the John’s line, we now have a large number of leads to follow and see if we can push back another generation from both Jacob and Mary. We now know enough to start targeting death certificates for both, which may contain critical names, as well as 6 more marriage/death certificates to look for Mary’s maiden name, as well pieces of evidence that link our Jacob to the arrival Jacob. And, DNA Painter has greatly narrowed down where we’re targeting our on-going research to finally break down this brick wall.
We also have about 20 trees integrated into the master tree, and all of their owners are likely working towards the same goal as we are. As they do their research, and new DNA matches are added to the mix over the years, it’s likely one of us is going to have that piece of the puzzle we’re missing, and finally put it all together.
Once you have all of your hints with notes attached, look for your largest unidentified match that has a Public Tree, even if it’s unlinked. Since the tree has no hints you’ll know their tree doesn’t match yours (yet!), but the larger the amount of cM the closer your match…so the fewer relatives you’ll have to build out.
Before we dive in with our first example, here’s the first of several surprising truths about doing genealogical DNA work: you will spend most of your time doing other people’s trees. In a perfect world your DNA match built out their tree to their 4xGGP too…but you’ll find most times you won’t be so lucky!
DNA match surprise #1: You will spend most of your time making DNA matches building out other people’s trees.
Example #1: Eileen Wilson
As an example, let’s look at a match with an Unlinked Tree and 242 cM of shared DNA. Looking at the match’s Public Tree, the names don’t jump out (other than the very common “Smith”), but based on our notes, we know it’s on Michael’s Father’s Mother’s Mother’s Father’s line…which was William Arthur Smith. To confirm, we entered the cM in the DNA Painter Shared cM Project tool (Link), and the results (eliminating the ½ siblings) indicate the most likely matches are from our tester’s Grandparents or Great Grandparents.
Expanding our tree, we see that we had already identified Wallace David Smith in our tree, his wife Mabel, as the brother of William Arthur Smith. We also had their daughter Lula, which all of which sync’s up with the match’s tree. From there, it’s pretty easy to prove out that the DNA match is the daughter of George and Lula (Smith) Hopkins.
This is the same process whether the DNA match is 242 cM or 12 cM: use common matches to narrow which line the DNA likely matches you, identify the most likely target for your match through tools like the Shared cM Project charts and the “What are the odds?” tool. From there, build out the likely tree based on your estimates until you find the match. Then, you update the notes so when you find another shared match, you’ll have the info to narrow down their DNA line!
Make sure to make a note in your match, as we did in Part 2 of this series, so you’ll be able to focus in on other matches with less shared DNA later.
Let’s try one more match that’s a little further out.
Example #2: “A.G.”
The next target is going to “A.G.”, a woman that shares 26cM with the same tester as the first example. The first thing we do is review A.G.’s shared matches with us, and we see notes indicating that the match is on our tester’s Father’s side, so we just narrowed our focus to that ½ of the tree. Next, we went to DNA Painter Shared cM Project tool and maped out the most likely matches for the level of shared cM, which shows that it’s likely our shared match is around a 4th Cousin, Once removed or a 5th Cousin. This means, it’s most likely we’re looking for 3x/4x GGP as our MRCA.
The good news is that we have a strong tree to 3x/4x GGP’s for our tester. The bad news is, we have no tree for A.G. and we’re going to have to build hers out to understand where we match. We followed our own instructions on building out a “quick and dirty” Ancestry tree (Building a good Public Ancestry.com tree – Part One: sources, citations, facts, and proof), especially paying attention to find proof of relationships between each generation. And, in the end, after about 16 hours of total work we found…nothing. No match.
Which brings us to our second of our surprising truths about doing genealogical DNA work: Your DNA matches will mostly be on family lines you already have great information on, and conversely most of your unlinked DNA matches will be on family lines which are already your brickwalls.
DNA match surprise #2: Your DNA matches will mostly be on family lines you already have great information on, and conversely most of your unlinked DNA matches will be on family lines which are already your brickwalls.
In this case, we have limitations on several key areas of our family tree. Our tester is Michael’s grandmother, and on her paternal line we run into a pretty solid brickwall at her 2x GGP. They likely were born in either New Hampshire or Vermont, before they migrated to Michigan through New York, but 3 generations of family historians haven’t gotten past Alvin Jewell (1830-1911). In A.G.’s line, there are two couples from Vermont, from about that time, but there’s not enough evidence to pursue a solid line of inquiry.
This brings us to of our third surprising truths about doing genealogical DNA work: Even with the best of trees, and hours of effort, you’re going to have a lot of matches that you’re not going to be able to link to your tree.
DNA match surprise #3: Even with the best of trees, and hours of effort, you’re going to have a lot of matches that you’re not going to be able to link to your tree.
This is also where the limitations of AncestryDNA start to become apparent. There are nearly no tools there to help us determine which side of our match’s line do we expect we match. How can we leverage DNA triangulation to further narrow down where we should be researching? When you’re trying to figure out where to look amongst 32 GGP’s who might be a key to your DNA match, being able to eliminate ½ of those potential matches is a huge boon. But, beyond what we’ve already gone through, there’s not much more they can offer.
One of the other limitations of AncestryDNA is that you can never prove your matches. Even in our first example, we have a good tree match, and the amount of shared DNA (242 cM) matches exactly where we’d expect the two samples to match (2nd Cousins), but without tools like a chromosome browser, it’s impossible to prove those two kits match as we’ve assumed.
We’ll be looking at other tools in later installments, including how we can narrow down the search for our MCRA link to A.G.
In our next installment we’re going to go through a GREAT set of tools in GEDmatch that will demonstrate what we wish we had in Ancestry, and we’ll show you how to leverage you DNA results there to really unlock your matches.
Deed Books are a great tool to move forward some of your most stubborn research questions, and there is a great deal of data in them, but without a tool like DeedMapper you’re likely not going to get the full picture of what’s found in them!
On Michael’s paternal line, the Tradewell’s are one of the two brickwalls left on that side of the tree…which is all the more ironic because the matriarch of family history research on that line was Myra (Tradewell) Morse (1870-1962). In all of her genealogy notes, and DAR applications, and family history presentations she never recorded the name of her Great Grandfather…and thus we have a brick wall.
About a year and a half ago we wrote about discovering formal genealogical “Research Reports” (Elizabeth Shown Mills has just the right guidance at just the right time!) and started drafting them for our toughest cases. Of course, the Tradewell line was the first subject. We knew that James B Tradewell is our 4x GGF and that he arrived in Racine County, Wisconsin Territory ca. 1844, where he and his wife Catherine lived until their deaths. We also knew that there was an Ephraim Tradewell, and his wife Marina, also arrived in Racine County around 1844, and that both men listed New York as their birth location. A little research showed that there were a James B and Ephraim Tradewell in Schoharie County, New York for the 1820, 1830, and 1840 U.S. Census but each disappeared after that and no further records were found for them there.
We wrote an “Analysis and Research Plan” for them, and it laid out the following questions we’d hoped to answer:
Were the James B and Ephraim Tradewell in Wisconsin from after 1844 the same men as those listed in the 1820-1840 U.S. Census in Schoharie County, New York?
Were they related, and/or did they even know each other?
Who was each of their fathers, and was either of those persons the brickwall 5x GGF?
Reviewing the Schoharie County Deed Books for 1797-1850 gave us some of the answers, and DeedMapper filled in a major piece of the puzzle.
Were the Wisconsin Tradewells the same as the New York Tradewells?
The answer is now a proven yes! Deeds were usually recorded with the Husband as the only purchaser, but almost always the wife is listed when a property is sold. In fact, every Deed we reviewed where we know we had an ancestor selling property, the wife isn’t just listed, there’s a statement from the County Clerk that recorded the deed that the wife was taken aside out of the presence of her husband to confirm she was willingly agreeing to the transaction. Besides making us wonder if any wife EVER felt empowered enough to say “no”, several sales gave us the names of the New York Tradewell’s wives: James B Tradewell was married to Catherine (Edwards) Tradewell, and Ephraim was married to Marina Tradewell. A perfect match!
We also saw a clean break in New York, with the last Tradewell land transaction completed in the summer of 1842, and the first Wisconsin transaction being conducted in 1844.
Were James and Ephraim related, and/or did they even know each other?
We still do not know if they were related, but we know they were likely very close and in fact lived next to each other…and we never would have known that without DeedMaker. Just reviewing the Deed Books, we learned that they were involved in one land transaction that indicates they were likely in a close relationship. On 7 April 1838 James sold Lot #7 of “Tradewell’s Tavern Stand” in Gilboa, NY to Ephraim for $200. Two weeks later, on 21 April 1838 Ephraim sold the same property to Sidney Tuttle for $200. We’re not sure exactly what was going on there, but it’s very likely there was coordination between the men for this to occur.
But what really sold us on DeedMapper, was what happened when we mapped all the plots we discovered in the 1797-1845 Deed Books. The biggest breakthrough came when we first mapped two properties, with no common points in their Legal Description, and they clearly fit together. Without sharing Metes & Bounds points in the description (like a Willow Tree), there’s no easy way to determine how they relate, but when you map them visually you can see them like jigsaw puzzle pieces and get a great feeling of location for the land.
Once we had those two properties mapped (both were owned by James B Tradewell and recorded in 1806), we drew another plot owned by Ephraim (recorded 1834) and we immediately knew they lived together as neighbors with an adjoining property line.
Here is the first Legal Description for James’ largest plot:
Beginning at a Willow tree near the Schoharie Creek marked on the east side with the Letters C.E. and runs thence south 15 degrees east 10 chains and 60 links, thence East 25 chains, thence north 21 degrees 30 minutes east 32 Chains, thence north 10 chains 50 links, thence west 17 chains and 50 links to the Schoharie creek, thence along said creek to the place of beginning containing 117 acres of land be the same more or less.
And here is the Legal Description for Ephraim’s plot:
Beginning at a hemlock sapling on the East side of Schoharie Creek marked on 4 sides with 3 notches and a blaze on the North side B.H, on the South side I.D. and runs thence North 30 degrees East 8 chains, thence, North 24 degrees West 12 chains, thence, due West 25 chains, thence, North 15 West 10 chains 60 links, thence, South 41 degrees West 12 chains to the west side of said creek, thence, South 2 degrees West 5 chains 75 links, hence, North 52 degrees East 2 chains, thence South 62 degrees East 6 chains to the North East side of said creek, thence, up said creek to the place of beginning.
These two plots, recorded almost 30 years apart, and showing no common marker other than Schoharie Creek, when drawn, revealed just how closely these men lived:
The beauty of DeedMapper is that this is first time we worked with Metes & Bounds land descriptions, the first time we’d recorded large amounts of deed information, and this was the 3rd time we’d ever entered information into the software. We literally knew almost nothing about what we were doing, and DeedMapper brought home how closely these men lived.
Now, it doesn’t prove James and Ephraim were related, and it’s likely only DNA will ever do that, but there is now no question these men had a close relationship. They weren’t distant cousins that lived miles apart in the same County, their families lived right next to each other.
Who was their father?
We still don’t know. This creek that’s referenced in so many of the deeds was dammed up in the 1920’s to provide drinking water to New York City, and all of this land is under a reservoir. However, that project caused the local Gilboa cemetery to be relocated, which gave us strong evidence that our 5x GGP were Reuben and Esther Tradewell, and if we can ever prove that James and Ephraim were brothers, we’ll then likely know Ephraim’s father too.
So, Deed Books are a great tool to move forward some of your most stubborn research questions, and there is a great deal of data in them, but without a tool like DeedMapper you’re likely not going to get the full picture of what’s found in them!