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Detecting sample swaps in diverse NGS data types using linkage disequilibrium.

Nauman JavedYossi FarjounTim J FennellCharles B EpsteinBradley E BernsteinNoam Shoresh
Published in: Nature communications (2020)
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.
Keyphrases
  • rna seq
  • single cell
  • high throughput
  • electronic health record
  • genome wide
  • big data
  • machine learning
  • gene expression
  • dna methylation
  • nucleic acid
  • neural network
  • artificial intelligence