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
Browse package contents
Package details |
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| Bioconductor views | Bayesian DifferentialExpression MassSpectrometry Normalization Proteomics QualityControl Regression Software |
| Maintainer | |
| License | GPL-3 |
| Version | 1.17.1 |
| URL | https://github.com/const-ae/proDA |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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