Stanford University professors Lawrence Wein and Mine Su Ertürk are the two scientists who had applied their mathematical expertise to improve forensic processes such as fingerprint, sexual assault kits and ballistics analysis has identified their next area of interest that is ‘forensic genetic genealogy’.
The duo is aiming at maximizing the probability of finding a descendant solution in the shortest time possible. In fact, in simulated runs using data from the DNA Doe Project (DDP), the team solved cases 10 times faster than the current average.
In a typical genetic genealogy investigation, the DNA sample is first taken from the unidentified remains or the samples from the suspect left at the scene of crime. The DNA profile is uploaded into a DNA database that generates a list of “matches” which is where the puzzle starts for genealogists. It is a puzzle because the matches could be in hundreds or thousands, usually distant cousins whose shared ancestors may have died more than a century ago.
By analysing such huge data, the genealogists construct a massive family tree that ties the far-flung relatives to the person who supplied the sample DNA. But, it’s not immediately apparent which matches will provide the best path to the target. And this may take thousands of hours to work upon.
While this method has seemingly worked since it took off in 2018, Wein says the “decentralization” of the technique is a fault that can be improved through mathematics. He said, “You have a team of people doing this and they will each decide to take a match to investigate, and then they’ll go off on their own to try to build a family tree backward in time from each match. They’re not thinking about the big picture holistically. Basically, we’re telling them, ‘Given where you are in the search right now, this is what you should do next’.”
Wein and Ertürk published their work in Journal of Forensic science, which says that they used simulated versions of 17 DNA Doe Project cases, 8 solved and 9 unsolved; each case analyzed had between 200 and 5,000 matches.
The new Proposed Method finds the most recent common ancestor between a match and the unknown target. After identifying a list of possible most recent common ancestors, the method “aggressively” fills out the family tree with their descendants, even if there’s only a slight chance that the target’s ancestor is on the list.
Ertürk explains, “We do this by describing the reconstructed family tree as a collection of probabilities that represent how likely each person on our tree is to be a correct ancestor of the target. Then, looking at these probabilities, you can tell which parts of the tree you should explore more.”
The study conducted by Wein and Ertürk concludes that this method can solve a case with a 7,500 person family tree around 94% of the time and the standard method’s success rate in those cases is about 4%.
Wein says, “In no way is our algorithm meant to substitute for genealogists. But if they’re really stuck, it will give them some ideas that may not be obvious.”
This genealogy technique was first used in 2018 to solve a 1981 murder case. A young, anonymous murder victim was found outside Dayton, Ohio, wearing a deer-hide poncho and for 37 she had been known as the ‘Buckish girl’.
Then, in April 2018, police announced that the mystery of her identity had been solved. Her name was Marcia L. King, and she had been identified by linking a snippet of her DNA to one of her cousins. Since then, forensic genetic genealogy has cleared more than 400 cases in the US. Yet this detective work is complex and time-consuming.