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proDA

This is the development version of proDA; for the stable release version, see proDA.

Differential Abundance Analysis of Label-Free Mass Spectrometry Data

Bioconductor version: Development (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")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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 1.15.0
In Bioconductor since BioC 3.10 (R-3.6) (4 years)
License GPL-3
Depends
Imports stats, utils, methods, BiocGenerics, SummarizedExperiment, S4Vectors, extraDistr
Linking To
Suggests testthat (>= 2.1.0), MSnbase, dplyr, stringr, readr, tidyr, tibble, limma, DEP, numDeriv, pheatmap, knitr, rmarkdown, BiocStyle
System Requirements
Enhances
URL https://github.com/const-ae/proDA
Bug Reports https://github.com/const-ae/proDA/issues
See More
Depends On Me
Imports Me MatrixQCvis
Suggests Me protti
Links To Me
Build Report  

Package Archives

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

Source Package proDA_1.15.0.tar.gz
Windows Binary proDA_1.15.0.zip
macOS Binary (x86_64) proDA_1.15.0.tgz
macOS Binary (arm64) proDA_1.15.0.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