Update on the moFF Algorithm for Label-Free Quantitative Proteomics

J Proteome Res. 2019 Feb 1;18(2):728-731. doi: 10.1021/acs.jproteome.8b00708. Epub 2018 Dec 14.

Abstract

moFF is a modular and operating-system-independent tool for quantitative analysis of label-free mass-spectrometry-based proteomics data. The moFF workflow, comprising matching-between-runs and apex quantification, can be applied to any upstream search engine's output, along with the corresponding Thermo or mzML raw file. We here present moFF 2.0, with improvements in speed through multithreading, the use of a new raw file access library, and a novel filtering approach in the matching-between-runs module. This filter allows moFF to correctly identify features that are present in one run but not in another, as demonstrated using spiked-in iRT peptides. Moreover, moFF 2.0 also provides a new peptide summary export that can be used in downstream statistical analysis. moFF is open source and freely available and can be downloaded from https://github.com/compomics/moFF.

Keywords: MS1-peptide intensity; bioinformatics tool; label-free quantification; singleton peptides.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms*
  • Data Analysis
  • Data Interpretation, Statistical*
  • Peptides / analysis
  • Peptides / chemistry
  • Proteomics / methods*
  • Software

Substances

  • Peptides