On this episode of CSI: New software sorts through ‘murky’ DNA mixtures

Has your DNA ever showed up at the scene of a murder but you had nothing to do with it? We hope not, but if so, you can now breathe a little easier as new forensic software will help track genetic evidence to protect the innocent from false accusations.

Appearing in the journal Forensic Science International: Genetics in May, Catherine Grgicak, assistant professor of biomedical forensic sciences at Boston University, and collaborators at Rutgers University and the Massachusetts Institute of Technology have developed NOCIt and MATCHit—forensic software to assist in identification the possible number of contributors through DNA.

NOCIt (NOC = number of contributors), uses statistical analysis to analyze and estimate the number of people whose DNA is included in the evidence, stating a probability from between one to five contributors.

MATCHit software compares DNA evidence to DNA from the suspect to create a match statistic, or “likelihood ratio,” to assign now much this person’s genetic makeup was found at the crime scene.

Grgicak’s team hopes to combine the two forensic lab softwares into a single tool by 2017.

How does the NOCIt software work?

Since the rise of DNA forensic science during the 1980s, tests have slowly become more sensitive in testing not only blood, but skin cells, too.

“Mixture analysis is a murky part of DNA forensics,” stated Greg Hampikian, a forensic biologist at Boise State University in Idaho. “Errors in DNA forensics can be multiplied in the justice system,” often leading to weak evidence being backed by science. The results? The increased possibility of false accusations.

Seeing NOCIt’s potential, the Department of Defense contracted out Grgicak’s lab to turn their once NOCIt prototype into something that can be utilized nationwide.

“There are no national guidelines or standards saying that labs have to meet some critical threshold of a match statistic,” to conclude that a possible suspect had been at a crime scene, explained Grgicak.

This is where the new software comes into play: In testing mock evidence, NOCIt may find that one genetic mixture is 99.9 percent likely to have two contributors, while another may have a 35 percent likelihood of three contributors. These percentages help identify the possible number of contributors to the crime—something vital in determining a guilty party.

The future of MATCHit and the judicial system

The goal for Grgicak’s team through forensic software is to increase the certainty of identifying a suspect’s DNA at the crime scene. While MATCHit is still a work in progress, Grgicak hopes it will become an important tool in all forensic labs.

In terms of its algorithm, MATCHit works with the number of contributors and commonality of DNA variations in the general population in the hopes of providing a match statistic. Then, going further as a software, MATCHit provides a “p value,” a common statistical measure to indicate how likely it would be for a random person’s DNA to match more strongly than the current suspect’s. In testing the software with one, two, and three people so far, Grgicak’s team has seen positive results.

But with the new software advances in DNA analysis spewing out numbers, one question is left on everyone’s minds: how far will forensic labs go in interpreting this data and these probabilities?

“We know, at least from our own early tests of MATCHit, that we have not falsely included individuals using that threshold,” concludes Grgicak, “and that’s the most important thing.”

Backed by funding from the US Department of Justice and Department of Defense, the rest of the nation is hopeful that with these new softwares, forensic teams will be able to find the guilty party and protect those who were innocent out from behind bars.


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