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Am J Hum Genet. 2012 Nov 2;91(5):839-48. doi: 10.1016/j.ajhg.2012.09.004. Epub 2012 Oct 25.

Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data.

Author information

  • 1Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.

Abstract

DNA sample contamination is a serious problem in DNA sequencing studies and may result in systematic genotype misclassification and false positive associations. Although methods exist to detect and filter out cross-species contamination, few methods to detect within-species sample contamination are available. In this paper, we describe methods to identify within-species DNA sample contamination based on (1) a combination of sequencing reads and array-based genotype data, (2) sequence reads alone, and (3) array-based genotype data alone. Analysis of sequencing reads allows contamination detection after sequence data is generated but prior to variant calling; analysis of array-based genotype data allows contamination detection prior to generation of costly sequence data. Through a combination of analysis of in silico and experimentally contaminated samples, we show that our methods can reliably detect and estimate levels of contamination as low as 1%. We evaluate the impact of DNA contamination on genotype accuracy and propose effective strategies to screen for and prevent DNA contamination in sequencing studies.

Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

PMID:
23103226
[PubMed - indexed for MEDLINE]
PMCID:
PMC3487130
Free PMC Article

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