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proDA

Differential Abundance Analysis of Label-Free Mass Spectrometry Data


Bioconductor version: Release (3.18)

Account for missing values in label-free mass spectrometry data without imputation. The package implements a probabilistic dropout model that ensures that the information from observed and missing values are properly combined. It adds empirical Bayesian priors to increase power to detect differentially abundant proteins.

Author: Constantin Ahlmann-Eltze [aut, cre] , Simon Anders [ths]

Maintainer: Constantin Ahlmann-Eltze <artjom31415 at googlemail.com>

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

Installation

To install this package, start R (version "4.3") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("proDA")

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

Documentation

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

browseVignettes("proDA")
Data Import HTML R Script
Introduction HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Bayesian, DifferentialExpression, MassSpectrometry, Normalization, Proteomics, QualityControl, Regression, Software
Version 1.16.0
In Bioconductor since BioC 3.10 (R-3.6) (4.5 years)
License GPL-3
Depends
Imports stats, utils, methods, BiocGenerics, SummarizedExperiment, S4Vectors, extraDistr
System Requirements
URL https://github.com/const-ae/proDA
Bug Reports https://github.com/const-ae/proDA/issues
See More
Suggests testthat (>= 2.1.0), MSnbase, dplyr, stringr, readr, tidyr, tibble, limma, DEP, numDeriv, pheatmap, knitr, rmarkdown, BiocStyle
Linking To
Enhances
Depends On Me
Imports Me MatrixQCvis
Suggests Me protti
Links To Me
Build Report Build Report

Package Archives

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

Source Package proDA_1.16.0.tar.gz
Windows Binary proDA_1.16.0.zip
macOS Binary (x86_64) proDA_1.16.0.tgz
macOS Binary (arm64) proDA_1.16.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/proDA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/proDA
Bioc Package Browser https://code.bioconductor.org/browse/proDA/
Package Short Url https://bioconductor.org/packages/proDA/
Package Downloads Report Download Stats