PrInCE: An R/Bioconductor package for protein-protein interaction network inference from co-fractionation mass spectrometry data

Michael A. Skinnider, Charley Cai, R. Greg Stacey, Leonard J. Foster

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)2775-2777
Number of pages3
JournalBioinformatics
Volume37
Issue number17
DOIs
StatePublished - Sep 1 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Molecular Biology
  • Biochemistry
  • Statistics and Probability
  • Computer Science Applications
  • Computational Theory and Mathematics

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