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.

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Bibliographic Details
Main Authors: Nauman Javed, Yossi Farjoun, Tim J. Fennell, Charles B. Epstein, Bradley E. Bernstein, Noam Shoresh
Format: article
Language:EN
Published: Nature Portfolio 2020
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Online Access:https://doaj.org/article/3aac3ad4af5c44bbbcff502de0819ea0
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Summary: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.