PeptideWitch - a software package to produce high-stringency proteomics data visualizations from label-free shotgun proteomics data

David C. L. Handler, Flora Cheng, Abdulrahman M. Shathili, Paul A. Haynes*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
1 Downloads (Pure)

Abstract

PeptideWitch is a python-based web module that introduces several key graphical and technical improvements to the Scrappy software platform, which is designed for label-free quantitative shotgun proteomics analysis using normalised spectral abundance factors. The program inputs are low stringency protein identification lists output from peptide-to-spectrum matching search engines for 'control' and 'treated' samples. Through a combination of spectral count summation and inner joins, PeptideWitch processes low stringency data, and outputs high stringency data that are suitable for downstream quantitation. Data quality metrics are generated, and a series of statistical analyses and graphical representations are presented, aimed at defining and presenting the difference between the two sample proteomes.

Original languageEnglish
Article number21
Pages (from-to)1-11
Number of pages11
JournalProteomes
Volume8
Issue number3
DOIs
Publication statusPublished - Sep 2020

Bibliographical note

Copyright the Author(s) 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Label-free shotgun proteomics
  • False discovery rate
  • Data quality
  • Protein quantitation
  • Spectral counting

Fingerprint Dive into the research topics of 'PeptideWitch - a software package to produce high-stringency proteomics data visualizations from label-free shotgun proteomics data'. Together they form a unique fingerprint.

Cite this