A computational approach for positive genetic identification and relatedness detection from low-coverage shotgun sequencing data.

Several methods exist for detecting genetic relatedness or identity by comparing DNA information. These methods generally require genotype calls, either SNPs or STRs, at the sites used for comparison. For some DNA samples, like those obtained from bone fragments or single rootless hairs, there is often not enough DNA present to generate genotype calls that are accurate and complete enough for these comparisons. Here, we describe IBDGem, a fast and robust computational procedure for detecting genomic regions of identity-by-descent by comparing low-coverage shotgun sequence data against genotype calls from a known query individual. At less than 1x genome coverage, IBDGem reliably detects segments of relatedness and can make high-confidence identity detections with as little as 0.01x genome coverage.