HOMER
Software for motif discovery and next-gen sequencing analysis
HOMER Motif Discovery and Analysis
HOMER contains a novel motif discovery algorithm that was
designed for regulatory element analysis in genomics
applications (DNA only, no protein). It is a
differential motif discovery algorithm, which means that it
takes two sets of sequences and tries to identify the
regulatory elements that are specifically enriched in one
set relative to the other. It uses ZOOPS scoring (zero
or one occurrence per sequence) and assumes motif
occurrences will follow the hypergeometric distribution (or
binomial) to determine motif enrichment. HOMER also
tries its best to account for undesired sequence bias that
may be present in the target sequences relative to the
background/control sequences. Ultimately, it was designed
with ChIP-Seq and promoter/regulatory element analysis in
mind, but can be applied to a wide variety of DNA motif
finding problems.There are several ways to perform motif analysis with HOMER. The links below introduce the various workflows for running motif analysis. In a nutshell, HOMER contains two tools, findMotifs.pl and findMotifsGenome.pl, that manage all the steps for discovering motifs in promoter and genomic regions, respectively. These scripts attempt to make it easy for the user to analyze a list of genes or genomic positions for enriched motifs. However, if you already have the sequence files that you want to analyze (i.e. FASTA files), findMotifs.pl (and homer2) can process these directly.
New to v5, HOMER/HOMER2 now has methods to select and model background sequences in the genome that match positional biases in the target sequences. This includes the ability to model distance-dependent features within sequences.
Basic description of HOMER's
motif discovery approach
Analyzing lists of genes with promoter motif analysis (findMotifs.pl)
Analyzing genomic positions [e.g. ChIP-seq, ATAC-seq] (findMotifsGenome.pl)
Analyzing custom FASTA files (findMotifs.pl, homer2)
Analyzing data for RNA motifs (findMotifs.pl/findMotifsGenome.pl)
Advanced selection of background sequences (homer2 background)
New motif analysis approaches that examine positional enrichment (pacifierHomer2.pl, createHomer2EnrichmentTable.pl, MEPP)
Scanning for motif across the entire genome (scanMotifGenomeWide.pl)
Analyzing lists of genes with promoter motif analysis (findMotifs.pl)
Analyzing genomic positions [e.g. ChIP-seq, ATAC-seq] (findMotifsGenome.pl)
Analyzing custom FASTA files (findMotifs.pl, homer2)
Analyzing data for RNA motifs (findMotifs.pl/findMotifsGenome.pl)
Advanced selection of background sequences (homer2 background)
New motif analysis approaches that examine positional enrichment (pacifierHomer2.pl, createHomer2EnrichmentTable.pl, MEPP)
Scanning for motif across the entire genome (scanMotifGenomeWide.pl)
Additional Motif Analysis Approaches from the Benner Lab:
MEIRLOP: Instead of performing target vs. background motif enrichment (e.g. HOMER), MEIRLOP will regress motif occurrence against a set of 'scored' sequences (i.e. regulatory elements ranked/scored by their fold-change) [by Nathan Delos Santos].
MEPP: Similar to MEIRLOP above, MEPP will regress motif occurrence against a set of scored sequences, but will do it in a position-dependent manner [by Nathan Delos Santos].
Can't figure something out? Questions, comments, concerns, or other feedback:
cbenner@ucsd.edu