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

Ma, Wenxiu, Noble, William S. and Bailey, Timothy L. (2014) Motif-based analysis of large nucleotide data sets using MEME-ChIP. Nature Protocols, 9 6: 1428-1450. doi:10.1038/nprot.2014.083


Author Ma, Wenxiu
Noble, William S.
Bailey, Timothy L.
Title Motif-based analysis of large nucleotide data sets using MEME-ChIP
Journal name Nature Protocols   Check publisher's open access policy
ISSN 1754-2189
1750-2799
Publication date 2014-01-01
Year available 2014
Sub-type Article (original research)
DOI 10.1038/nprot.2014.083
Open Access Status Not yet assessed
Volume 9
Issue 6
Start page 1428
End page 1450
Total pages 23
Place of publication London, United Kingdom
Publisher Nature Publishing Group
Language eng
Subject 1300 Biochemistry, Genetics and Molecular Biology
2700 Medicine
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.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
Institute for Molecular Bioscience - Publications
 
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