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HOMER (Hypergeometric Optimization of Motif EnRichment) is
a suite of tools for Motif Discovery and next-gen sequencing
analysis. It is a collection of command line programs
for UNIX-style operating systems written in Perl and C++.
HOMER was primarily written as a de novo motif discovery algorithm and is
well suited for finding 8-20 bp motifs in large scale
genomics data. HOMER contains many useful tools for
analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and
numerous other types of functional genomics sequencing data
sets.
News
(10-24-2019)
New version
(v4.11) Added
routines for
csRNA-seq
(TSS)
analysis.
Documentation
is here,
paper here.
(10-24-2019)
Updated
genome-wide
motif
prediction
tracks (see
below)
(04-01-2019)
Check out Metascape for
gene
enrichment and
functional
analysis (paper).
(5-16-2018) New version of HOMER
(v4.10). First official
update in a while, many new
features and fixes, including
better support for replicate
experiments, normalization
options, super enhancers, etc.
Also, a large portion of the
documentation has also been
updated. Many Hi-C analysis
routines have been extensively
upgraded.
Old News
Program Download
Download
Page - Get the latest version of HOMER
Supported
Organisms: Human (hg18, hg19, hg38),
Mouse (mm8, mm9, mm10), Rat (rn4, rn5, rn6), Frog
(xenTro2, xenTro3), Zebrafish (danRer7),
Drosophila (dm3), C elegans (ce6, ce10), S.
cerevisiae (sacCer2, sacCer3), pombe (ASM294v1),
Arabidopsis (tair10), Rice (msu6), and also works
with custom genomes in FASTA format and gene
annotations in GTF format.
Using HOMER
Introduction to
HOMER
Duff-sponsored Tutorials
HOMER
Hi-C Analysis Tutorial [PDF-old]
Description of routines for analysis of Hi-C
data to study genome conformation and structure.
Doughnut Documentation
Primary Motif Data
HOMER Known Motifs - Genome-wide predictions and UCSC
Track
Data included in HOMER that may be useful for other
purposes
Credits
HOMER was developed
primarily by Chris Benner, with significant contributions
and suggestions by Sven Heinz, Max Chang, Kasey Hutt, Yin
Lin, Gene Hsiao, Fernando Alcalde, Josh Stender, Amy
Sullivan, Nathan Spann, Ivan Garcia-Bassets, Michael Lam,
Michael Rehli, and many others. Initial supervision
for the project was provided by Professors Christopher K.
Glass and Shankar Subramaniam.
Development of HOMER is carried out in the Benner Lab at
UCSD, and has been previously been developed in the
Integrative Genomics and
Bioinformatics Core at the Salk Institute and the Glass
Lab at UCSD.
If you use HOMER in your research, generally it is
appropriate to cite the following paper:
Heinz
S, Benner C, Spann N, Bertolino E et al. Simple Combinations of
Lineage-Determining Transcription Factors Prime
cis-Regulatory Elements Required for Macrophage and B
Cell Identities. Mol Cell
2010 May 28;38(4):576-589. PMID: 20513432
For certain specialized analysis, it may be
more appropriate to cite one of the following papers:
csRNA-seq/TSS analysis: PMID:NA,
Hi-C: PMID:30146161,
PMID:26417104,
PMID:23064439,
GRO-seq: PMID:21572438
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