MEME-ChIP: Motif analysis of large DNA datasets

Machanick, Philip and Bailey, Timothy L. (2011) MEME-ChIP: Motif analysis of large DNA datasets. Bioinformatics, 27 12: 1696-1697. doi:10.1093/bioinformatics/btr189


Author Machanick, Philip
Bailey, Timothy L.
Title MEME-ChIP: Motif analysis of large DNA datasets
Journal name Bioinformatics   Check publisher's open access policy
ISSN 1367-4811
1367-4803
Publication date 2011-06-15
Sub-type Article (original research)
DOI 10.1093/bioinformatics/btr189
Open Access Status Not yet assessed
Volume 27
Issue 12
Start page 1696
End page 1697
Total pages 2
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Subject 1303 Biochemistry
1312 Molecular Biology
1703 Computational Theory and Mathematics
1706 Computer Science Applications
2605 Computational Mathematics
2613 Statistics and Probability
2700 Medicine
Abstract Motivation: Advances in high-throughput sequencing have resulted in rapid growth in large, high-quality datasets including those arising from transcription factor (TF) ChIP-seq experiments. While there are many existing tools for discovering TF binding site motifs in such datasets, most web-based tools cannot directly process such large datasets.Results: The MEME-ChIP web service is designed to analyze ChIP-seq 'peak regions'-short genomic regions surrounding declared ChIP-seq 'peaks'. Given a set of genomic regions, it performs (i) ab initio motif discovery, (ii) motif enrichment analysis, (iii) motif visualization, (iv) binding affinity analysis and (v) motif identification. It runs two complementary motif discovery algorithms on the input data-MEME and DREME-and uses the motifs they discover in subsequent visualization, binding affinity and identification steps. MEME-ChIP also performs motif enrichment analysis using the AME algorithm, which can detect very low levels of enrichment of binding sites for TFs with known DNA-binding motifs. Importantly, unlike with the MEME web service, there is no restriction on the size or number of uploaded sequences, allowing very large ChIP-seq datasets to be analyzed. The analyses performed by MEME-ChIP provide the user with a varied view of the binding and regulatory activity of the ChIP-ed TF, as well as the possible involvement of other DNA-binding TFs.
Formatted abstract
Motivation: Advances in high-throughput sequencing have resulted in rapid growth in large, high-quality datasets including those arising from transcription factor (TF) ChIP-seq experiments. While there are many existing tools for discovering TF binding site motifs in such datasets, most web-based tools cannot directly process such large datasets.
Results: The MEME-ChIP web service is designed to analyze ChIP-seq ‘peak regions’—short genomic regions surrounding declared ChIP-seq ‘peaks’. Given a set of genomic regions, it performs (i) ab initio motif discovery, (ii) motif enrichment analysis, (iii) motif visualization, (iv) binding affinity analysis and (v) motif identification. It runs two complementary motif discovery algorithms on the input data—MEME and DREME—and uses the motifs they discover in subsequent visualization, binding affinity and identification steps. MEME-ChIP also performs motif enrichment analysis using the AME algorithm, which can detect very low levels of enrichment of binding sites for TFs with known DNA-binding motifs. Importantly, unlike with the MEME web service, there is no restriction on the size or number of uploaded sequences, allowing very large ChIP-seq datasets to be analyzed. The analyses performed by MEME-ChIP provide the user with a varied view of the binding and regulatory activity of the ChIP-ed TF, as well as the possible involvement of other DNA-binding TFs.
Availability: MEME-ChIP is available as part of the MEME Suite at http://meme.nbcr.net.
Contact: t.bailey@uq.edu.au
Supplementary information: Supplementary data are available at Bioinformatics online.
Q-Index Code CX
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Non HERDC
Institute for Molecular Bioscience - Publications
 
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Created: Tue, 25 Oct 2011, 03:53:40 EST by Dr Timothy Bailey on behalf of School of Chemistry & Molecular Biosciences