Archive | September 2017

Solving unknown parentage cases with DNA

In the last few months, I have helped solve five out of six unknown parentage cases in just a few weeks from mainly third and fourth cousin matches. How? By using the GWorks automation from DNAgedcom combined with AncestryDNA results. These searches used to take many months, even years, with much tedious spreadsheeting and segment analysis. What has changed?

Well, Ancestry.com now has a database of over 5 million tests plus software to connect trees and DNA. This can make the search easy for Americans without having to use the segment data.

My attempt to explain the technique I use of combining GWorks with mirror trees met with glazed eyes in my Adoption workshop last June. I thought my previous write-up was pretty clear but I have not heard back from anyone saying that it had worked for them. So I am trying again with this post today.

In an unknown parentage search, the object is to find a common ancestral couple among your DNA matches and build a tree of their descendants until you find someone in the right place at the right time. It seems pretty obvious to me that an automated way to compare trees is best; followed by surname frequencies to check for the spouses, in order to figure out which lines to follow. So why does everyone tune out when I try to explain how to do that with GWorks? Too many steps? Too geeky?

By using GWorks to find a likely ancestral couple, I have been able to build down to the grandparents or great grandparents of the adoptee fairly quickly. Then I build the trees back in time for each child’s spouse to find the most likely line. At this point I start using “mirror” or research trees.

Here is the step-by-step approach:

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How to Help Houston with DNA test purchases

The company that started the personal DNA testing revolution, Family Tree DNA, is displaying this banner on their home page.

That’s right, their headquarters are in Houston and they are donating a portion of their sales in September for Hurricane Harvey relief.

Bennett Greenspan, ftDNA CEO points out the Tecan machine, which adds chemicals to extract the DNA

So if you were dithering about testing your Y, or buying an upgrade to the tests you have done, now is the time to go for it. Also their kit uses a cheek swab which is much easier for your elderly relatives than the spit kits from other companies, plus they preserve the DNA for future tests. So get some of their autosomal test kits too (“family finder” kits). Stock up!

In that same spirit, I will also donate all of the September affiliate income that I get when you click on my links to Family Tree DNA and then buy from their site. (Yes their name is always an affiliate link.)

In case you missed it, I got a wonderful tour of their facility when I visited in 2015 and can vouch that their 8th floor, North loop location is free of flooding. However many of their employees were affected and I heard tales of 4 and 5 hour commutes initially. Today, for some, the commute was almost normal. Houston strong!

The 25% relationship: a first look at the data

A question I often get is “Can you tell if this DNA match is my uncle or my half-brother?”  Why this question? Because it is very difficult to tell the difference between a half sibling and a nibling (an aunt/uncle/niece/nephew) relationship from the amount of matching DNA. Like grandparents, they all share 25% with you, or about 1750 centimorgans (cMs) give or take several hundred. Unlike grandparents, the age difference can’t usually be used to tell them apart. The testing companies might call him “close family”, “first cousin,” “uncle,” or the more descriptive “1st Cousin, Half Siblings, Grandparent/ Grandchild, Aunt/ Niece” from Family Tree DNA, which by the way is my Dad’s actual great-niece’s designation. Then they show you the amount of shared DNA in centimorgans and maybe a percentage, but really they are just making an educated guess about the relationship.

I wanted to find a way to help adoptees figure out more accurately which relationship a new 25% match was likely to be, so I collected detailed statistics using a google form for about a year, getting some 2400 responses. These were self-reported from people who read my blog or are members of groups on Facebook where I publicized this. I am still collecting, so feel free to add yours to my form (click here) to get included in the next report. GEDmatch numbers preferred.

My experience from helping people understand their DNA results had led me to suspect that segment sizes were the key to telling these relationships apart. I had noticed that the sizes of the four largest segments would usually be much much larger for half siblings than niblings. However now that I have these crowd-sourced numbers, I can see that much of my personal experience came from helping with paternal side cases. There the segments are consistently much larger.

Can you tell a nibling from a half sib by the shared number of segments and centimorgans?

The collected wisdom of the many adoption search angels is that the number of segments can indicate the difference. While this usually works for nibling versus grandparent, half siblings too often seem to fall in the range of one or the other.

The DNA adoption folk have a chart which shows the number of segments expected for each relationship (click here for that PDF) which is very useful, just not enough for determining half siblings. They carefully separate the AncestryDNA results which can have more segments and fewer total centimorgans due to the removal of some matching data deemed less significant. DNA adoption also has an automated relationship estimater based on that data.

Leah Larkin recently wrote a fascinating post – Escape from the Overlap Zone – which showed simulations for these relationships which indicate that grandparents can easily be told from niblings since they have far fewer total segments. However again, the simulations show that half sibs and niblings have considerable overlap.

So how does the collected data compare?

Here is a scatter diagram graphing total centimorgans (X axis) versus number of segments (Y axis) for just grandparent and nibling relationships. This used only the GEDmatch data for consistency. The niblings are the lavender color and the dark results show where they overlap with the beige-pink colored grandparents. This is not far different from the predictions although there is more overlap than expected but look what happens when I add the half-sibling data below right.

The graph is hard to read now since those results overlap both categories. The colors are semi-transparent so the darker areas are created by having multiple colors in that area. There seems to be considerably more overlap than the simulations predicted.

It looks like just using just shared centimorgans and number of segments will not produce a clear answer as to whether a 25% relationship is a half sibling.

Notice the funny shape of the half sibling blues. There is a bunch on top with the niblings and another group with the grandparents. Fortunately someone had suggested that I include a question asking which side a relationship is on, paternal or maternal.
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