Detecting sample swaps in diverse NGS data types using linkage disequilibrium

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.

Bibliographic Details
Main Authors: Nauman Javed, Yossi Farjoun, Tim J. Fennell, Charles B. Epstein, Bradley E. Bernstein, Noam Shoresh
Format: Article
Language:English
Published: Nature Portfolio 2020-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-020-17453-5
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author Nauman Javed
Yossi Farjoun
Tim J. Fennell
Charles B. Epstein
Bradley E. Bernstein
Noam Shoresh
author_facet Nauman Javed
Yossi Farjoun
Tim J. Fennell
Charles B. Epstein
Bradley E. Bernstein
Noam Shoresh
author_sort Nauman Javed
collection DOAJ
description 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.
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spelling doaj.art-3aac3ad4af5c44bbbcff502de0819ea02022-12-21T18:01:42ZengNature PortfolioNature Communications2041-17232020-07-011111810.1038/s41467-020-17453-5Detecting sample swaps in diverse NGS data types using linkage disequilibriumNauman Javed0Yossi Farjoun1Tim J. Fennell2Charles B. Epstein3Bradley E. Bernstein4Noam Shoresh5Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical SchoolBroad Institute of MIT and HarvardBroad Institute of MIT and HarvardBroad Institute of MIT and HarvardDepartment of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical SchoolBroad Institute of MIT and HarvardParallelized 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.https://doi.org/10.1038/s41467-020-17453-5
spellingShingle Nauman Javed
Yossi Farjoun
Tim J. Fennell
Charles B. Epstein
Bradley E. Bernstein
Noam Shoresh
Detecting sample swaps in diverse NGS data types using linkage disequilibrium
Nature Communications
title Detecting sample swaps in diverse NGS data types using linkage disequilibrium
title_full Detecting sample swaps in diverse NGS data types using linkage disequilibrium
title_fullStr Detecting sample swaps in diverse NGS data types using linkage disequilibrium
title_full_unstemmed Detecting sample swaps in diverse NGS data types using linkage disequilibrium
title_short Detecting sample swaps in diverse NGS data types using linkage disequilibrium
title_sort detecting sample swaps in diverse ngs data types using linkage disequilibrium
url https://doi.org/10.1038/s41467-020-17453-5
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