Rxivist logo

Factorbook Motif Pipeline: A de novo motif discovery and filtering web server for ChIP-seq peaks

By Bong-Hyun Kim, Jiali Zhuang, Jie Wang, Zhiping Weng

Posted 04 Dec 2015
bioRxiv DOI: 10.1101/033670

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

Download data

  • Downloaded 558 times
  • Download rankings, all-time:
    • Site-wide: 66,816
    • In bioinformatics: 6,356
  • Year to date:
    • Site-wide: 106,843
  • Since beginning of last month:
    • Site-wide: 82,030

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


PanLingua

News