HOMER (v4.11, 10-24-2019)

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 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.


(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.


Introduction to HOMER

Duff-sponsored Tutorials

General Introduction to Next-Gen Sequencing Analysis Tutorial
Useful for those new to sequencing
HOMER Next-gen Sequencing Tutorial [PDF-old]

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

Old tutorial: Analysis of ChIP-Seq experiments using HOMER (some of this is out-of-date)

HOMER Motif Finding Tutorial

Instructions and advice for finding enriched regulatory elements from a set of genome positions, a list of genes, or raw FASTA files.
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

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


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

Link to the raw data: GSE21512
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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