const-ae/proDA: Differential Abundance Analysis of Label-Free Mass Spectrometry Data

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.

Getting started

Package details

Bioconductor views Bayesian DifferentialExpression MassSpectrometry Normalization Proteomics QualityControl Regression Software
Maintainer
LicenseGPL-3
Version1.3.1
URL https://github.com/const-ae/proDA
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("const-ae/proDA")
const-ae/proDA documentation built on July 23, 2020, 9:04 p.m.