Detecting sample swaps in diverse NGS data types using linkage disequilibrium

Nauman Javed; Yossi Farjoun; Tim J. Fennell; Charles B. Epstein; Bradley E. Bernstein; Noam Shoresh

doi:10.1038/s41467-020-17453-5

Nature Communications (Jul 2020)

Detecting sample swaps in diverse NGS data types using linkage disequilibrium

Nauman Javed,
Yossi Farjoun,
Tim J. Fennell,
Charles B. Epstein,
Bradley E. Bernstein,
Noam Shoresh

Affiliations

Nauman Javed: Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School
Yossi Farjoun: Broad Institute of MIT and Harvard
Tim J. Fennell: Broad Institute of MIT and Harvard
Charles B. Epstein: Broad Institute of MIT and Harvard
Bradley E. Bernstein: Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School
Noam Shoresh: Broad Institute of MIT and Harvard

DOI: https://doi.org/10.1038/s41467-020-17453-5
Journal volume & issue: Vol. 11, no. 1
pp. 1 – 8

Abstract

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Parallelized analysis in clinical genomics can lead to sample or data mislabelling, and could have serious downstream consequences. Here the authors present a tool to quantify sample genetic relatedness and detect such mistakes, and apply it to thousands of datasets from the ENCODE consortium.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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