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 (3.21)
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:
Maintainer: Constantin Ahlmann-Eltze <artjom31415 at googlemail.com>
citation("proDA")):
Installation
To install this package, start R (version "4.5") 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 | ||
| NEWS | Text |
Details
| biocViews | Bayesian, DifferentialExpression, MassSpectrometry, Normalization, Proteomics, QualityControl, Regression, Software |
| Version | 1.21.0 |
| In Bioconductor since | BioC 3.10 (R-3.6) (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_1.21.0.tar.gz |
| Windows Binary (x86_64) | |
| macOS Binary (x86_64) | |
| macOS Binary (arm64) | |
| 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 |