HOMER protocols

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HOMER specifications


Unique identifier OMICS_00483
Alternative name Hypergeometric Optimization of Motif EnRichment
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes


  • annotatePeaks
  • compareMotifs
  • findMotifs
  • findMotifsGenome
  • findPeaks
  • scanMotifGenomeWide



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  • person_outline Christopher Glass <>
  • person_outline Christopher Benner <>

Publication for Hypergeometric Optimization of Motif EnRichment

HOMER in pipelines

PMCID: 5768180
PMID: 29367853
DOI: 10.3389/fimmu.2017.01938

[…] (rpkm) (). the qc report, processed read count table, rpkm table, and interactive data exploring tool generated by quickrnaseq is available at https://baohongz.github.io/irf5_knockdown. we used homer () for pathway analysis as it contains a program for performing functional enrichment analysis from a list of genes (http://homer.ucsd.edu/homer/microarray/go.html) homer uses a one-sided […]

PMCID: 5778122
PMID: 29403501
DOI: 10.3389/fimmu.2018.00022

[…] sequence using the star (version 2.5.1) aligner software (). to measure differential gene expression, deseq2 () with the default parameters was used. the rna-seq experiments were visualized using homer () after custom tracks were prepared for the ucsc genome browser., the reverse transcription of the rna samples was performed as previously described (). qrt-pct was performed using an abi-7500 […]

PMCID: 5785540
PMID: 29371665
DOI: 10.1038/s41467-017-02740-5

[…] raw sequence files (.fastq files). reads were mapped to the mouse mm10 genome (ncbi build 37) using tophat version 2 (http://ccb.jhu.edu/software/tophat). the aligned reads were counted with the homer software (analyzerepeats.pl) and differentially regulated genes were identified using edger. as a threshold for degs we chose p value < 10−5, minimum 50 reads, and fold change excluding […]

PMCID: 5785540
PMID: 29371665
DOI: 10.1038/s41467-017-02740-5

[…] the standard illumina protocol (hiseq2000, single read, 50 bp v3), and mapped to the mouse mm10 reference genome by bowtie. data were further analyzed using the peak finding algorithm macs 1.4.2. homer software was used to annotate peaks, and all peaks with false discovery rate <1% were included. the uniquely mapping locations were used to generate the genome-wide intensity profiles, […]

PMCID: 5786002
PMID: 29374152
DOI: 10.1038/s41467-017-02762-z

[…] as significant. dmrs spanning <10 cpgs were rejected., for visualization, we merged the results of biological replicates and smoothened the data using a running average of three cpgs., we used homer to perform a de novo motif analysis using the “size given” option. great was used to identify genes in proximity (≤10 kb) to lmrs and to annotate genes within regulatory domains of snps. […]

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HOMER in publications

PMCID: 5955993
PMID: 29769529
DOI: 10.1038/s41467-018-04426-y

[…] bedtools package to generate a combinational peak set for following annotation and computation of peak descriptors. peaks were assigned to genes with tss closest to center of the peak region using homer. peak height, area, and width were computed on this combinational peak set using the extended reads coverage files (that is, number of fragments extended from chip-seq reads mapped to each base […]

PMCID: 5953949
PMID: 29765016
DOI: 10.1038/s41467-018-04234-4

[…] max = 1000, nstart = 100”. k-means clusters were annotated for enrichment of transcription factor motifs by determining the genome-wide binding motifs of transcription factors defined by the software homer, using the function “scanmotifsgenomewide.pl” and then testing for overrepresentation in each k-means group using fisher’s exact test. transcription factor footprinting was calculated by countin […]

PMCID: 5954019
PMID: 29765032
DOI: 10.1038/s41467-018-03781-0

[…] chip-seq, enriched peaks were called by macs2 with p-value <10−4 as cutoff, then peaks with q-value less than 0.01 were chosen for further analysis. peaks were assigned to the nearby genes by annotatepeaks.pl function in the homer package. candidate target genes were identified if the peaks were located within ±2.5 kb of their tsss. the density of histone signal was normalized […]

PMCID: 5953939
PMID: 29765031
DOI: 10.1038/s41467-018-04310-9

[…] (ipa) (qiagen redwood city) was used for pathway analysis. finally, pathways were prioritized based on their frequency in the enriched clusters., motif analysis was performed in 13 clusters using homer. due to small input regions, q-value of 0.1 was used as the cutoff of known motif enrichment. de novo motif was also discovered and scores were calculated indicating matches to known motifs. de […]

PMCID: 5951854
PMID: 29760437
DOI: 10.1038/s12276-018-0091-4

[…] condition-specific expression was defined as showing a 1.0 log2-fold difference and p-adj < 0.01 in expression between mtb rv and mtb ra. rna-seq experiments were normalized and visualized using homer after preparing custom tracks for the ucsc genome browser (http://genome.ucsc.edu/)., for immunohistochemistry analysis of tissue sections, murine lungs were fixed in 10% formalin and embedded […]

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HOMER institution(s)
Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA; Department of Medicine, University of California, San Diego, La Jolla, CA, USA; Section of Molecular Biology, University of California, San Diego, La Jolla, CA, USA; Molecular Genetics and Cell Biology, The University of Chicago, Chicago, IL, USA; Department of Discovery Immunology, Genentech, San Francisco, CA, USA; Section of Experimental Haematology, University of Leeds, Leeds, UK
HOMER funding source(s)
Supported by an NIH postdoctoral training grant and by NURSA consortium grant No DK62434 and further supported by NIH grants (HC088093, DK063491, CA52599, P50 GM081892-01A1) and a Foundation Leducq Transatlantic Network Grant.

HOMER reviews

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Gyan Prakash Mishra

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HOMER suite is most widely used for ChIPseq data analysis. Simple command line exposure is sufficient enough to utilize its full potential for diverse array of analysis such as binding region identification (both for TF and histone) , motif analysis, comparison of peaks from multiple experiment and many more.


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One of the best tool for ChIPseq analysis along with downstream analysis till Motif searching and many more.