SMaSH: Sample matching using SNPs in humans.

ABSTRACT:

Background

Inadvertent sample swaps are a real threat to data quality in any medium to large scale omics studies. While matches between samples from the same individual can in principle be identified from a few well characterized single nucleotide polymorphisms (SNPs), omics data types often only provide low to moderate coverage, thus requiring integration of evidence from a large number of SNPs to determine if two samples derive from the same individual or not.

Methods

We select about six thousand SNPs in the human genome and develop a Bayesian framework that is able to robustly identify sample matches between next generation sequencing data sets.

Results

We validate our approach on a variety of data sets. Most importantly, we show that our approach can establish ide

SUBMITTER: Westphal M 

PROVIDER: S-EPMC6936078 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature