Dec 4, 2015

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

BioRxiv : the Preprint Server for Biology
Bong-Hyun KimZhiping Weng

Abstract

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

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Mentioned in this Paper

Statistical Test
Chromatin Immunoprecipitation
Sequencing
Protein Domain
Analysis
High-Throughput RNA Sequencing
Protein Interaction Motifs
Physiological Processes

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