Diagenode

SMaSH: Sample matching using SNPs in humans.


Westphal M, Frankhouser D, Sonzone C, Shields PG, Yan P, Bundschuh R

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 identity between different omics data types such as Exome, RNA-Seq, and MethylCap-Seq. We demonstrate how identity detection degrades with sample quality and read coverage, but show that twenty million reads of a fairly low quality RNA-Seq sample are still sufficient for reliable sample identification. CONCLUSION: Our tool, SMASH, is able to identify sample mismatches in next generation sequencing data sets between different sequencing modalities and for low quality sequencing data.

Tags
MethylCap
IP-Star Compact

Share this article

Published
December, 2019

Source

Products used in this publication

  • Methylation kit icon
    C02020010
    MethylCap kit
  • some alt
    B03000002
    IP-Star® Compact Automated System

Events

  • EpiChrom
    Umea Sweden
    Feb 27-Feb 28, 2020
 See all events

News

 See all news


The European Regional Development Fund and Wallonia are investing in your future.

Extension of industrial buildings and new laboratories.



  ABOUT SSL CERTIFICATES

       Site map   |   Contact us   |   Conditions of sales   |   Conditions of purchase   |   Privacy policy   |   Diagenode Diagnostics