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HOMER (v5.1, 7-16-2024)

Software for motif discovery and next generation sequencing analysis

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 mostly in Perl and C++, although some functionality requires additional tools to be installed as well (e.g. samtools, R, etc.). 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

(07-16-2024) HOMER2 - new version (v5.1). Improvements to some command structure, documentation, data/annotation updates.

(04-25-2024) HOMER2 - new version (v5). Added additional support for positional sequence analysis, including expanded options for background sequence selection and modeling and variant analysis. For more information on these updates, see the HOMER2 page.

(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).

 Old News

Program Download

Download Page - Get the latest version of HOMER (Distributed under GPLv3)

Supported Organisms: Most HOMER tools will work with any FASTA or GTF file, however, additional annotation support is included/available for 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).

Using HOMER

Introduction to HOMER


Duff-sponsored Tutorials

HOMER Motif Discovery and Analysis
Instructions and advice for finding enriched regulatory elements from a set of genome locations, a list of genes, or raw FASTA files.
HOMER Next-gen Sequencing Tutorial

Helps guide and explain how to use HOMER for csRNA-seq/ChIP-Seq/GRO-Seq/MNase-Seq/DNase-Seq/RNA-Seq/Hi-C etc. analysis

Primary Motif Data

HOMER Known Motifs - Genome-wide predictions and UCSC Track

These tracks display motif positions genome-wide for human and mouse.  They are based on HOMER-motifs, and certainly miss many "weak" binding sites and incorrectly predict others.  However, the predictions can still serve as a useful guide to where transcription factors have the potential to bind (if they're expressed in the system you're studying).

Human hg38 UCSC BigBed Track 191020 (load as a custom track) - [primary BED file]
Human hg19 UCSC BigBed Track 191020 (load as a custom track) - [primary BED file]

Mouse mm10 UCSC BigBed Track 191020 (load as a custom track) - [primary BED file]
Mouse mm9 UCSC BigBed Track 191020 (load as a custom track) - [primary BED file]

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, Sascha Duttke, 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: 31649059, Hi-C: PMID:30146161, PMID:26417104, PMID:23064439, GRO-seq: PMID:21572438
Can't figure something out? Questions, comments, concerns, or other feedback:
cbenner@ucsd.edu