We present PrInCE, an R/Bioconductor package that employs a machine-learning approach to infer protein- protein interaction networks from co-fractionation mass spectrometry (CF-MS) data. Previously distributed as a collection of Matlab scripts, our ground-up rewrite of this software package in an open-source language dramatically improves runtime and memory requirements. We describe several new features in the R implementation, including a test for the detection of co-eluting protein complexes and a method for differential network analysis. PrInCE is extensively documented and fully compatible with Bioconductor classes, ensuring it can fit seamlessly into existing proteomics workflows.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics