proDA

This package is for version 3.21 of Bioconductor; for the stable, up-to-date release version, see proDA.

Differential Abundance Analysis of Label-Free Mass Spectrometry Data

Bioconductor version: 3.21

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] ORCID iD ORCID: 0000-0002-3762-068X , Simon Anders [ths] ORCID iD ORCID: 0000-0003-4868-1805

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

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

Installation

To install this package, start R (version "4.5") 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

Need some help? Ask on the Bioconductor Support site!

Details

biocViews Bayesian, DifferentialExpression, MassSpectrometry, Normalization, Proteomics, QualityControl, Regression, Software

Version 1.22.1

In Bioconductor since BioC 3.10 (R-3.6) (6 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

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_1.22.1.tar.gz

Windows Binary (x86_64) proDA_1.22.1.zip

macOS Binary (x86_64) proDA_1.22.1.tgz

macOS Binary (arm64) proDA_1.22.1.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

Old Source Packages for BioC 3.21 Source Archive