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a tool to perform statistical analysis of differential protein expression for quantitative proteomics data.

Bioconductor version: Release (3.19)

DEqMS is developped on top of Limma. However, Limma assumes same prior variance for all genes. In proteomics, the accuracy of protein abundance estimates varies by the number of peptides/PSMs quantified in both label-free and labelled data. Proteins quantification by multiple peptides or PSMs are more accurate. DEqMS package is able to estimate different prior variances for proteins quantified by different number of PSMs/peptides, therefore acchieving better accuracy. The package can be applied to analyze both label-free and labelled proteomics data.

Author: Yafeng Zhu

Maintainer: Yafeng Zhu <yafeng.zhu at>

Citation (from within R, enter citation("DEqMS")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

DEqMS R Markdown vignettes HTML R Script
Reference Manual PDF


biocViews Bayesian, DifferentialExpression, ExperimentHubSoftware, ImmunoOncology, MassSpectrometry, MultipleComparison, Normalization, Preprocessing, Proteomics, Software
Version 1.22.0
In Bioconductor since BioC 3.8 (R-3.5) (5.5 years)
License LGPL
Depends R (>= 3.5), graphics, stats, ggplot2, matrixStats, limma(>= 3.34)
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Suggests BiocStyle, knitr, rmarkdown, markdown, plyr, reshape2, farms, utils, ggrepel, ExperimentHub, LSD
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Follow Installation instructions to use this package in your R session.

Source Package DEqMS_1.22.0.tar.gz
Windows Binary
macOS Binary (x86_64) DEqMS_1.22.0.tgz
macOS Binary (arm64) DEqMS_1.22.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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