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. © 2014 Hashimoto et al.
CITATION STYLE
Hashimoto, T. B., Edwards, M. D., & Gifford, D. K. (2014). Universal Count Correction for High-Throughput Sequencing. PLoS Computational Biology, 10(3). https://doi.org/10.1371/journal.pcbi.1003494
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