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

NCJ Number
307465
Author(s)
Remy Nguyen; Joshua D Kapp; Samuel Sacco; Steven P Myers; Richard E Green
Date Published
June 2023
Length
9 pages
Annotation

This article describes a computational procedure called IBDGem that detects genomic regions of identity-by-descent through comparison of low-coverage shotgun sequence data against genotype calls from a known query individual.

Abstract

This article describes 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 1× genome coverage, IBDGem reliably detects segments of relatedness and can make high-confidence identity detections with as little as 0.01× genome coverage. Several methods exist for detecting genetic relatedness or identity by comparing DNA information. These methods generally require genotype calls, either single-nucleotide polymorphisms or short tandem repeats, 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. (Published Abstract Provided)