Introduction

Precise regulatory control of genes, particularly in eukaryotes, frequently requires the joint action of multiple sequence-specific transcription factors. A cis-regulatory module (CRM) is a genomic locus that is responsible for gene regulation and that contains multiple transcription factor binding sites in close proximity. Given a collection of known transcription factor binding motifs, many bioinformatics methods have been proposed over the past 15 years for identifying within a genomic sequence candidate CRMs consisting of clusters of those motifs.The MCAST algorithm uses a hidden Markov model with a P-value-based scoring scheme to identify candidate CRMs. Here, we introduce a new version of MCAST that offers improved graphical output, a dynamic background model, statistical confidence estimates based on false discovery rate estimation and, most significantly, the ability to predict CRMs while taking into account epigenomic data such as DNase I sensitivity or histone modification data. We demonstrate the validity of MCAST's statistical confidence estimates and the utility of epigenomic priors in identifying CRMs.MCAST is part of the MEME Suite software toolkit. A web server and source code are available at http://meme-suite.org and http://alternate.meme-suite.orgt.bailey@imb.uq.edu.au or william-noble@uw.eduSupplementary data are available at Bioinformatics online.

Publications

  1. MCAST: scanning for cis-regulatory motif clusters.
    Cite this
    Grant CE, Johnson J, Bailey TL, Noble WS, 2016-04-01 - Bioinformatics (Oxford, England)
  2. Searching for statistically significant regulatory modules.
    Cite this
    Bailey TL, Noble WS, 2003-10-01 - Bioinformatics (Oxford, England)

Credits

  1. Charles E Grant
    Developer

    Department of Genome Sciences, University of Washington, United States of America

  2. James Johnson
    Developer

    Institute for Molecular Bioscience, The University of Queensland, Australia

  3. Timothy L Bailey
    Developer

    Institute for Molecular Bioscience, The University of Queensland, Australia

  4. William Stafford Noble
    Investigator

    Department of Genome Sciences, University of Washington, United States of America

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Summary
AccessionBT000803
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByWilliam Stafford Noble