Since its release nearly 2 years ago, What Are the Odds? (WATO) has become an essential tool for solving family mysteries with autosomal DNA (the kind tested by AncestryDNA, 23andMe, MyHeritage, Living DNA, and the “Family Finder” test at FamilyTreeDNA).
Briefly, someone with an unidentified parent, grandparent, or even great grandparent may have a set of DNA matches who are all from the same extended family. That is, how they all descend from a most recent common ancestor or couple (MRCA) is known, but how the original tester—or target—fits in is not. WATO lets you “try out” the target in different places and tells you which of those hypotheses are most likely, based on how much DNA the target shares with each of the people in the tree.
A Simple Example
Consider Julia, whose father is unknown. Julia has DNA matches to Dan and Jessie, who are first cousins through their grandmother Mabel and Mabel’s husband. She shares 1800 cM with Dan and 800 cM with Jessie. She also shares 225 cM with their second cousin, Michelle. Taken together, these matches tell me that Julia is descended from Mabel’s parents and almost certainly from Mabel herself. (All names and centimorgan amounts in this example are fabricated.)
The relationships among these matches tell me that Julia must be descended from Mabel’s parents, and based on how much DNA she shares with Dan and Jessie, she’s probably descended from Mabel herself. But how?
To use WATO, I can build a simple tree descendant tree from Mabel’s parents, assign centimorgan amounts to the people who have tested (Dan, Jessie, and Michelle), and then place hypotheses where I think Julia might fit. WATO automatically figures out which hypotheses don’t work (e.g., Julia can’t be Dan’s granddaughter), and which are most probable. In this case, WATO is telling us that it’s 111 times more likely that Julia is Dan’s half sister than his niece.
WHAT’S NEW IN WATO?
The new beta version of WATO has several major improvements. Some will be readily apparent to those who already use the tool, and some are less obvious. I’ll describe each of them below.
Bear in mind that this version of WATO has been tested by a group of about 15 people, but there are almost certainly bugs we didn’t catch or scenarios we didn’t consider. If you think you’ve found a bug, or simply want help using the tool, please join our Facebook group.
When you first access the new version of WATO, you’ll be greeted by this pop-up.
Note the very exciting “IMPORT A GEDCOM” button at the bottom. We no longer need to manually build out the descendant tree of the MRCA! (A gedcom file is a text version of your family tree. You can export one from the software you use to manage your tree.)
If you dismiss the popup, you can also upload a gedcom using the LOAD button in WATO’s toolbar.
Either route will take you to this pop-up. You can either drop a gedcom file into the window or click to browse for one on your storage device.
Once you’ve loaded your gedcom file, WATO will ask you to select the MRCA of the DNA matches.
You can make a choice about the how living people will be displayed in the tree, then click “IMPORT DESCENDANTS”.
My descendant tree for James Weicks had more than 100 people. Here’s what WATO imported in just moments. I had to split the image to display it all in one view. Can you imagine how long it would take to build this out manually?
Once you’ve imported a tree, you can manually enter the centimorgan amounts to each DNA match by hovering over a name, selecting “Enter Match cM”, and typing in the number. Do this for each match whose placement in the tree is known. You can use shared DNA amounts from any of the testing companies.
The next step in using WATO is to designate places you think the target person might fit into the tree. These are your hypotheses. WATO can now suggest them for you!
First, though, you need to tell WATO when your target person was born. That’s because WATO considers whether a potential parent was of age to have a child and whether they died before the child was conceived. Simply enter the birth year in the field at the top, then click the “SUGGEST HYPOTHESES” button.
Here’s a simplified version of the tree I imported, before and after the hypotheses are added. It’s nigh upon impossible to read at this resolution, but you can see that WATO has placed 42 hypotheses throughout the tree. It’s left out many other places where the score would be zero.
When we zoom in to a portion of the tree, we see that WATO has added full and half siblings as needed to generate hypotheses. That’s because the tree you import might not be filled in on all branches, and there may be family members you don’t know about.
You can still add or delete hypotheses manually wherever you like. If you’re absolutely certain, for example, that Edward only had one child, you could remove the “Unknown sibling” and “Unknown half-sib” individuals to simplify you tree. You can also remove all suggested hypotheses with a single mouse click.
The newest version of WATO also implements updated relationship probabilities from AncestryDNA. The key features of the new dataset are that the probabilities now extend down to 6 cM (previously 40 cM), they are shifted slightly, and the distributions are broader. You can learn more here.
A consequence of having broader cM distributions for each relationship is that hypotheses that were ruled out in the earlier version of WATO will be ever-so-slightly possible in this one. Because the scores in WATO are all relative to the least likely hypothesis, this has the effect of inflating the scores of better hypotheses to astronomical levels.
To correct for these misleadingly large values, this version of WATO now filters out extremely low scores. Any hypothesis that is a million times (or more) worse than the best hypothesis is ruled out. (As a reminder, this is a beta version of the tool, and the threshold for score filtering may be adjusted in the future. Feedback is appreciated.)
A hidden gem in the new version of WATO is the presence of spouse names. To see them, hover your cursor over a person in the tree. Spouses will be listed below the birth–death dates. To edit them, click the ADD/EDIT DETAILS button.
For now, spouse names are just for bookkeeping, but there are some interesting future applications that can be built off of them.
The green and red score flags associated with hypotheses in the tree have some new tweaks. Hover over a red flag (score = 0) and you’ll see this overlay:
It’s a great reminder to check your work. You wouldn’t want to rule out a valid hypothesis because of an error. If the tree checks out, you know that hypothesis is really not possible.
You can do the same with the green flags. The overlay calculates how much more likely the best hypothesis is than the next best one, and for weaker hypotheses, it tells you that the score is not significantly better than others.
And finally, if you click on the flag, WATO will take you to the Ranking of Hypotheses table below the tree, which ranks the hypotheses by score and summarizes them.
Feedback Is Appreciated
WATO v2 is still a beta version, meaning it’s been put through its paces by a small group of users (the alpha testing group), but there may well be programming bugs we didn’t find or user scenarios we didn’t consider. If you have problems with the tool, or just want a community to help you figure out how to use it, please join the DNA Painter: What Are the Odds? (WATO) group on Facebook. Tell them The DNA Geek send you!
- “What Are the Odds?” An online tool that can help solve DNA puzzles video by Jonny Perl
- Introduction to What Are the Odds? (WATO) video by The DNA Geek
- What Are the Odds? A tool for fitting a DNA match into a family tree video by Andrew Millard
- Improving the Odds blog
- The Limits of Predicting Relationships Using DNA blog
- Science the Heck Out of Your DNA—Part 1 blog
- Science the Heck Out of Your DNA—Part 2 blog
- Science the Heck Out of Your DNA—Part 3 blog
- Science the Heck Out of Your DNA—Part 4 blog
- Science the Heck Out of Your DNA—Part 5 blog
- Science the Heck Out of Your DNA—Part 6 blog
- Science the Heck Out of Your DNA—Part 7 blog