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PMID: 24853928 Published · ppublish English Journal Article Research Support, N.I.H., Extramural

Motif-based analysis of large nucleotide data sets using MEME-ChIP.

Nature protocols ·Vol. 9 ·No. 6 ·2014-00-00 ·Pages 1428-50

Ma W, Noble WS, Bailey TL

Abstract

MEME-ChIP is a web-based tool for analyzing motifs in large DNA or RNA data sets. It can analyze peak regions identified by ChIP-seq, cross-linking sites identified by CLIP-seq and related assays, as well as sets of genomic regions selected using other criteria. MEME-ChIP performs de novo motif discovery, motif enrichment analysis, motif location analysis and motif clustering, providing a comprehensive picture of the DNA or RNA motifs that are enriched in the input sequences. MEME-ChIP performs two complementary types of de novo motif discovery: weight matrix-based discovery for high accuracy; and word-based discovery for high sensitivity. Motif enrichment analysis using DNA or RNA motifs from human, mouse, worm, fly and other model organisms provides even greater sensitivity. MEME-ChIP's interactive HTML output groups and aligns significant motifs to ease interpretation. This protocol takes less than 3 h, and it provides motif discovery approaches that are distinct and complementary to other online methods.

MeSH Terms
Algorithms Binding Sites/genetics Chromatin Immunoprecipitation/methods Cluster Analysis High-Throughput Nucleotide Sequencing/methods Nucleotide Motifs/genetics Software
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Ma Wenxiu
Department of Genome Sciences, University of Washington, Seattle, Washington, USA.
Noble William S
1] Department of Genome Sciences, University of Washington, Seattle, Washington, USA. [2] Department of Computer Science and Engineering, University of Washington, Seattle, Washington, USA.
Bailey Timothy L
Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
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Article Info
Journal
Nature protocols
Abbr.
Nat Protoc
ISSN
1750-2799
Published
2014-00-00
Epub
2014-00-22
Pages
1428-50
Language
English
Region
England
NLM ID
101284307
PMCID
PMC4175909
Subset
IM
Grants
NIGMS NIH HHS · R01 GM098039 · United States
NIGMS NIH HHS · R01 GM103544 · United States
NCRR NIH HHS · R01 RR021692 · United States
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