On forensic likelihood ratios from low-coverage sequencing.

ABSTRACT: Advances in sequencing technology are allowing forensic scientists to access genetic information from increasingly challenging samples. A recently published computational approach, IBDGem, analyzes sequencing reads, including from low-coverage samples, in order to arrive at likelihood ratios for human identification. Here, we show that likelihood ratios produced by IBDGem are best interpreted as testing a null hypothesis different from the traditional one used in a forensic genetics context. In particular, rather than testing the hypothesis that the sample comes from a person unrelated to the person of interest, IBDGem tests the hypothesis that the sample comes from an individual who is included in the reference database used to run the method. This null hypothesis is not generally of fore

SUBMITTER: Ouerghi F 

PROVIDER: S-EPMC11160658 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature