Motif elucidation in ChIP-seq datasets with a knockout control

Abstract

Chromatin immunoprecipitation-sequencing (ChIP-seq) is widely used to find transcription factor binding sites, but suffers from various sources of noise. Knocking out the target factor mitigates noise by acting as a negative control. Paired wild-type and knockout experiments can generate improved motifs but require optimal differential analysis. We introduce peaKO--a computational method to automatically optimize motif analyses with knockout controls, which we compare to two other methods. PeaKO often improves elucidation of the target factor and highlights the benefits of knockout controls, which far outperform input controls. It is freely available at https://peako.hoffmanlab.org.