MEME-ChIP: motif analysis of large DNA datasets
Top Cited Papers
Open Access
- 12 April 2011
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 27 (12) , 1696-1697
- https://doi.org/10.1093/bioinformatics/btr189
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.Keywords
This publication has 10 references indexed in Scilit:
- DREME: motif discovery in transcription factor ChIP-seq dataBioinformatics, 2011
- Genome-wide identification of TAL1's functional targets: Insights into its mechanisms of action in primary erythroid cellsGenome Research, 2010
- Motif Enrichment Analysis: a unified framework and an evaluation on ChIP dataBMC Bioinformatics, 2010
- Assigning roles to DNA regulatory motifs using comparative genomicsBioinformatics, 2010
- JASPAR 2010: the greatly expanded open-access database of transcription factor binding profilesNucleic Acids Research, 2009
- RSAT: regulatory sequence analysis toolsNucleic Acids Research, 2008
- Trawler: de novo regulatory motif discovery pipeline for chromatin immunoprecipitationNature Methods, 2007
- Quantifying similarity between motifsGenome Biology, 2007
- MEME: discovering and analyzing DNA and protein sequence motifsNucleic Acids Research, 2006
- Combining evidence using p-values: application to sequence homology searches.Bioinformatics, 1998