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Tools for the Differential Analysis of Proteins Abundance with R

Bioconductor version: Release (3.19)

The package DAPAR is a Bioconductor distributed R package which provides all the necessary functions to analyze quantitative data from label-free proteomics experiments. Contrarily to most other similar R packages, it is endowed with rich and user-friendly graphical interfaces, so that no programming skill is required (see `Prostar` package).

Author: c(person(given = "Samuel", family = "Wieczorek", email = "", role = c("aut","cre")), person(given = "Florence", family ="Combes", email = "", role = "aut"), person(given = "Thomas", family ="Burger", email = "", role = "aut"), person(given = "Vasile-Cosmin", family ="Lazar", email = "", role = "ctb"), person(given = "Enora", family ="Fremy", email = "", role = "ctb"), person(given = "Helene", family ="Borges", email = "", role = "ctb"))

Maintainer: Samuel Wieczorek <samuel.wieczorek at>

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


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.


Reference Manual PDF


biocViews DataImport, GO, MassSpectrometry, Normalization, Preprocessing, Proteomics, QualityControl, Software
Version 1.36.2
In Bioconductor since BioC 3.2 (R-3.2) (9 years)
License Artistic-2.0
Depends R (>= 4.3.0)
Imports Biobase, MSnbase, DAPARdata(>= 1.30.0), utils, highcharter, foreach
System Requirements
Bug Reports
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Suggests testthat, BiocStyle, AnnotationDbi, clusterProfiler, graph, diptest, cluster, vioplot, visNetwork, vsn, igraph, FactoMineR, factoextra, dendextend, parallel, doParallel, Mfuzz, apcluster, forcats, readxl, openxlsx, multcomp, purrr, tibble, knitr, norm, scales, tidyverse, cp4p, imp4p (>= 1.1), lme4, dplyr, limma, preprocessCore, stringr, tidyr, impute, gplots, grDevices, reshape2, graphics, stats, methods, ggplot2, RColorBrewer, Matrix, org.Sc.sgd.db
Linking To
Depends On Me
Imports Me Prostar
Suggests Me DAPARdata, mi4p
Links To Me
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package DAPAR_1.36.2.tar.gz
Windows Binary (64-bit only)
macOS Binary (x86_64) DAPAR_1.36.2.tgz
macOS Binary (arm64) DAPAR_1.36.2.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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Old Source Packages for BioC 3.19 Source Archive