DREME: Motif discovery in transcription factor ChIP-seq data

Bailey, Timothy L. (2011) DREME: Motif discovery in transcription factor ChIP-seq data. Bioinformatics, 27 12: 1653-1659. doi:10.1093/bioinformatics/btr261

Author Bailey, Timothy L.
Title DREME: Motif discovery in transcription factor ChIP-seq data
Journal name Bioinformatics   Check publisher's open access policy
ISSN 1367-4803
Publication date 2011-06-15
Sub-type Article (original research)
DOI 10.1093/bioinformatics/btr261
Open Access Status Not yet assessed
Volume 27
Issue 12
Start page 1653
End page 1659
Total pages 7
Editor Joaquin Dopazo
Place of publication Oxford, U.K.
Publisher Oxford University Press
Language eng
Formatted abstract
Motivation: Transcription factor (TF) ChIP-seq datasets have particular characteristics that provide unique challenges and opportunities for motif discovery. Most existing motif discovery algorithms do not scale well to such large datasets, or fail to report many motifs associated with cofactors of the ChIP-ed TF.

Results: We present DREME, a motif discovery algorithm specifically designed to find the short, core DNA-binding motifs of eukaryotic TFs, and optimized to analyze very large ChIP-seq datasets in minutes. Using DREME, we discover the binding motifs of the the ChIP-ed TF and many cofactors in mouse ES cell (mESC), mouse erythrocyte and human cell line ChIP-seq datasets. For example, in mESC ChIP-seq data for the TF Esrrb, we discover the binding motifs for eight cofactor TFs important in the maintenance of pluripotency. Several other commonly used algorithms find at most two cofactor motifs in this same dataset. DREME can also perform discriminative motif discovery, and we use this feature to provide evidence that Sox2 and Oct4 do not bind in mES cells as an obligate heterodimer. DREME is much faster than many commonly used algorithms, scales linearly in dataset size, finds multiple, non-redundant motifs and reports a reliable measure of statistical significance for each motif found. DREME is available as part of the MEME Suite of motif-based sequence analysis tools (http://meme.nbcr.net).
Keyword Embryonic stem-cells
Factor-binding sites
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2012 Collection
Institute for Molecular Bioscience - Publications
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Citation counts: TR Web of Science Citation Count  Cited 304 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 311 times in Scopus Article | Citations
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Created: Tue, 25 Oct 2011, 03:40:36 EST by Dr Timothy Bailey on behalf of Institute for Molecular Bioscience