TY - JOUR T1 - Factorbook Motif Pipeline: A <em>de novo</em> motif discovery and filtering web server for ChIP-seq peaks JF - bioRxiv DO - 10.1101/033670 SP - 033670 AU - Bong-Hyun Kim AU - Jiali Zhuang AU - Jie Wang AU - Zhiping Weng Y1 - 2015/01/01 UR - http://biorxiv.org/content/early/2015/12/04/033670.abstract N2 - Summary High-throughput sequencing technologies such as ChIP-seq have deepened our understanding in many biological processes. De novo motif search is one of the key downstream computational analysis following the ChIP-seq experiments and several algorithms have been proposed for this purpose. However, most web-based systems do not perform independent filtering or enrichment analyses to ensure the quality of the discovered motifs. Here, we developed a web server Factorbook Motif Pipeline based on an algorithm used in analyzing ENCODE consortium ChIP-seq datasets. It performs comprehensive analysis on the set of peaks detected from a ChIP-seq experiments: (i) de novo motif discovery; (ii) independent composition and bias analyses and (iii) matching to the annotated motifs. The statistical tests employed in our pipeline provide a reliable measure of confidence as to how significant are the motifs reported in the discovery step.Availability Factorbook Motif Pipeline source code is accessible through the following URL. https://github.com/joshuabhk/factorbook-motif-pipeline ER -