Work

Detecting sample swaps in diverse NGS data types using linkage disequilibrium

Year: 2020

Type: article

Abstract: As the number of genomics datasets grows rapidly, sample mislabeling has become a high stakes issue. We present CrosscheckFingerprints (Crosscheck), a tool for quantifying sample-relatedness and detecting incorrectly paired sequencing datasets from different donors. Crosscheck outperforms similar methods and is effective even when data are sparse or from different assays. Application of Crosscheck to 8851 ENCODE ChIP-, RNA-, and DNase-seq datasets enabled us to identify and correct dozens of mislabeled samples and ambiguous metadata annotations, representing ~1% of ENCODE datasets.

Source: Nature Communications

DOI: 10.1038/s41467-020-17453-5

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

Institutions: Broad Institute, Harvard University, Massachusetts General Hospital

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $5,380

Funders: U.S. Department of Health and Human Services, National Human Genome Research Institute