const-ae/proDD: Identifying Differentially Abundant Proteins from Label-Free Mass Spectrometry Data

Implements a Bayesian model to identify proteins that are differentially abundant label-free mass spectrometry data. The empirical Bayesian model takes into account the missing observations which occur at low intensity using a probabilistic dropout model. It provides additional methods to estimate the dropout probability curves, the sample distances and other useful functions.

install.packages("remotes")
remotes::install_github("const-ae/proDD")