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Bioinformatics AdvancesBioinformaticsPeer-reviewed journal article

promor: a comprehensive R package for label-free proteomics data analysis and predictive modeling

Chathurani RanathungeiD, Sagar S. PateliD, Lubna Jahan Rashid PinkyiD, Vanessa L. Correll, Shimin CheniD, O. John Semmes, Robert K. ArmstrongiD, Charles Donald Combs, Julius O. NyalwidheiD

PDFDOIPreprintCode

Abstract

SummaryWe present promor, a comprehensive, user-friendly R package that streamlines label-free (LFQ) proteomics data analysis and building machine learning-based predictive models with top protein candidates. Availability and implementationpromor is freely available as an open source R package on the Comprehensive R Archive Network (CRAN)(https://CRAN.R-project.org/package=promor) and distributed under the Lesser General Public License (version 2.1 or later). Development version of promor is maintained on GitHub (https://github.com/caranathunge/promor) and additional documentation and tutorials are provided on the package website (https://caranathunge.github.io/promor/). Contactcaranathunge86@gmail.com

Citations
16
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1.38
Field percentile
top 22%

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