PLoS Computational Biology (Mar 2014)

Universal count correction for high-throughput sequencing.

  • Tatsunori B Hashimoto,
  • Matthew D Edwards,
  • David K Gifford

DOI
https://doi.org/10.1371/journal.pcbi.1003494
Journal volume & issue
Vol. 10, no. 3
p. e1003494

Abstract

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We show that existing RNA-seq, DNase-seq, and ChIP-seq data exhibit overdispersed per-base read count distributions that are not matched to existing computational method assumptions. To compensate for this overdispersion we introduce a nonparametric and universal method for processing per-base sequencing read count data called FIXSEQ. We demonstrate that FIXSEQ substantially improves the performance of existing RNA-seq, DNase-seq, and ChIP-seq analysis tools when compared with existing alternatives.