PT  - JOURNAL ARTICLE
AU  - André L. Martins
AU  - Ninad M. Walavalkar
AU  - Warren D. Anderson
AU  - Chongzhi Zang
AU  - Michael J Guertin
TI  - Universal correction of enzymatic sequence bias
AID  - 10.1101/104364
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 104364
4099  - http://biorxiv.org/content/early/2017/01/30/104364.short
4100  - http://biorxiv.org/content/early/2017/01/30/104364.full
AB  - Coupling molecular biology to high throughput sequencing has revolutionized the study of biology. Molecular genomics techniques are continually refined to provide higher resolution mapping of nucleic acid interactions and structure. Sequence preferences of enzymes can interfere with the accurate interpretation of these data. We developed seqOutBias to characterize enzymatic sequence bias from experimental data and scale individual sequence reads to correct intrinsic enzymatic sequence biases. SeqOutBias efficiently corrects DNase-seq, TACh-seq, ATAC-seq, MNase-seq, and PRO-seq data. Lastly, we show that seqOutBias correction facilitates identification of true molecular signatures resulting from transcription factors and RNA polymerase interacting with DNA.