proDA

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

All versions

3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10

Differential Abundance Analysis of Label-Free Mass Spectrometry Data

Bioconductor version: Development (3.24)

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

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

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

Constantin Ahlmann-Eltze. proDA: Differential Abundance Analysis of Label-Free Mass Spectrometry Data. doi:10.18129/B9.bioc.proDA, R package version 1.27.0, https://bioconductor.org/packages/proDA.

Generated from the package metadata; it may differ from the package's own citation.

Installation

To install this package, start R (version "4.6") and enter:

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

## The following initializes the development version of Bioconductor
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

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Bayesian, DifferentialExpression, MassSpectrometry, Normalization, Proteomics, QualityControl, Regression, Software
Version	1.27.0
In Bioconductor since	BioC 3.10 (R-3.6) (7 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, numDeriv, pheatmap, knitr, rmarkdown, BiocStyle
Linking To
Enhances
Depends On Me
Imports Me	MatrixQCvis, SmartPhos
Suggests Me	protti
Links To Me
Build Report	Build Report, r-universe

Package Archives

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

Source Package	proDA_1.27.0.tar.gz
Windows Binary (x86_64)	proDA_1.27.0.zip
macOS Binary (big-sur-x86_64)	proDA_1.27.0.tgz
macOS Binary (sonoma-arm64)	proDA_1.27.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/proDA
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/proDA
Package Short Url	https://bioconductor.org/packages/proDA/
Package Downloads Report	Download Stats