caranathunge/promor
A comprehensive R package for label-free proteomics data analysis and modeling
This tool helps life scientists, biochemists, and medical researchers analyze label-free quantitative (LFQ) proteomics data. It takes MaxQuant 'proteinGroups.txt' files or standard protein intensity matrices and experimental design files as input. The output includes insights into differentially expressed proteins and trained machine learning models for predicting biological outcomes, allowing for a streamlined workflow from raw data to biological understanding.
Use this if you need a comprehensive R package to analyze label-free proteomics data for differential expression and build predictive models using machine learning.
Not ideal if your proteomics data is not label-free quantification (LFQ) or if you are not comfortable working within the R environment.
Stars
16
Forks
5
Language
R
License
LGPL-2.1
Category
Last pushed
Nov 15, 2025
Commits (30d)
0
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