DESeq statistics

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Citations per year

Number of citations per year for the bioinformatics software tool DESeq

Tool usage distribution map

This map represents all the scientific publications referring to DESeq per scientific context
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Associated diseases

This word cloud represents DESeq usage per disease context

Popular tool citations

chevron_left Differential expression Differential abundant feature detection Normalization Normalization Differential expression detection chevron_right
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DESeq specifications


Unique identifier OMICS_01306
Name DESeq
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU Lesser General Public License version 3.0
Computer skills Advanced
Version 1.20.0
Stability Stable
methods, RColorBrewer, Biobase, IRanges, GenomicRanges, testthat, locfit, ggplot2, BiocParallel, S4Vectors(>=0.9.25), rmarkdown, knitr, genefilter, vsn, SummarizedExperiment(>=1.1.6), Hmisc, BiocGenerics(>=0.7.5), geneplotter, Rcpp(>=0.11.0), pheatmap, IHW, apeglm, ashr, tximport, tximportData, readr, pbapply, airway, pasilla(>=0.2.10)
Maintained Yes




No version available



  • person_outline Michael Love
  • person_outline Simon Anders

Additional information

An implementation for detection of differential translated genes using Ribo-seq is available at

Publication for DESeq

DESeq citations


Genomic alterations of ground glass nodular lung adenocarcinoma

Sci Rep
PMCID: 5955945
PMID: 29769567
DOI: 10.1038/s41598-018-25800-2

[…] riterion of a maximum read count >20 across all samples. Read counts were normalized by the trimmed mean of M-values normalization method. The differentially expressed genes were identified using the DESeq R package ( Gene set enrichment tests were performed using the GAGE R tool. Clustering was performed by principal component analysis and hierarchical clust […]


Integrated analysis of hepatic mRNA and miRNA profiles identified molecular networks and potential biomarkers of NAFLD

Sci Rep
PMCID: 5955949
PMID: 29769539
DOI: 10.1038/s41598-018-25743-8

[…] determined by reads per kilobase per million mapped reads. Hierarchical clustering of representative mRNAs and miRNAs expressions was performed to reveal reproducibility in biological replicates.The DESeq package was used to detect DEGs and DEMs between the normal and NAFLD groups, with thresholds of a two-fold change (the ratio between seven NAFLD rats’ and seven normal rats’ averaged signal val […]


Changes in genome organization of parasite specific gene families during the Plasmodium transmission stages

Nat Commun
PMCID: 5954139
PMID: 29765020
DOI: 10.1038/s41467-018-04295-5

[…] ial random variable, and we estimated the relationship between the mean and variance by grouping pairs of loci that are separated by the same linear genomic distance. We adapted the model employed by DESeq to Hi-C data by using an explicit specific scaling factor corresponding to bin-specific ICE biases. In addition, we estimated variance and dispersion of the negative binomial without replicates […]


Long non coding RNA expression patterns in lung tissues of chronic cigarette smoke induced COPD mouse model

Sci Rep
PMCID: 5954018
PMID: 29765063
DOI: 10.1038/s41598-018-25702-3

[…] Qualified RNA sequencing data were mapped to the mouse genome (GRCM38/mm10) and annotated using Tophat software. The expression levels of lncRNAs and mRNAs were normalized and tested using DESeq software. LncRNAs or mRNAs with fold change >2 and padj (value adjusted for multiple testing with the Benjamini-Hochberg procedure) <0.05 were defined as significantly differential expressed tra […]


“Tuberculosis in advanced HIV infection is associated with increased expression of IFNγ and its downstream targets”

BMC Infect Dis
PMCID: 5952419
PMID: 29764370
DOI: 10.1186/s12879-018-3127-4
call_split See protocol

[…] . Trimmed reads were mapped to the human genome GRCh38/hg19 with STAR [], and the expression level for each gene was counted with HTSeq [] according to gene annotations from Ensembl. The Bioconductor DESeq package in R [] was used to normalize the counts and call differential expressions. Principal Component Analysis (PCA) was used for data visualization. Hierarchical clustering was performed with […]


The lncRNA myocardial infarction associated transcript centric competing endogenous RNA network in non small cell lung cancer

PMCID: 5958945
DOI: 10.2147/CMAR.S163395

[…] ng to the histologic staging data. lncRNA and mRNA transcripts were annotated based on UCSC Genome Browser database ( database. After nor-malization of expression data, the DESeq package in R was used to identify the DEGs. Absolute fold change (including upregulation and downregulation) >2 and adjusted P-value < 0.05 were set as cutoffs. Co-expression network and importa […]

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DESeq institution(s)
Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA, USA; Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA; Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany; Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany
DESeq funding source(s)
Supported by a stipend from the International Max Planck Research School for Computational Biology and Scientific Computing, a grant from the National Institutes of Health (5T32CA009337-33), and the European Union’s 7th Framework Programme (Health) via Project Radiant.

DESeq reviews

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Anamaria Elek's avatar image No country

Anamaria Elek

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DESeq2 package in R is a first-choice for DE analysis


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DEseq2 is a very robust and fast package for differential gene expression analysis of RNA-seq data. It has a very intuitive pipeline to get most out of your data with few lines of code. The documentation is also pretty straightforward, I would only include more Case Studies, since the technique is used with many diverse experimental designs. On the other hand, Bioconductor mailing list and forums frequented by the author(s) help circuvemting this. In summary, is a must tool for a bioinformatician toolkit.