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

Chathurani Ranathunge, Sagar Patel, Lubna Pinky, Vanessa L. Correll, Shimin Chen, O. John Semmes, Robert Armstrong, C. Donald Combs, Julius O. Nyalwidhe

2023Bioinformatics Advances14 citationsDOIOpen Access PDF

Abstract

Summary: We present promor, a comprehensive, user-friendly R package that streamlines label-free quantification proteomics data analysis and building machine learning-based predictive models with top protein candidates. Availability and implementation: promor 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/). Supplementary information: online.

Topics & Concepts

R packageMIT LicenseComputer scienceDocumentationLicenseSource codeOpen sourceInformation retrievalSoftwareProgramming languageOperating systemAdvanced Proteomics Techniques and ApplicationsMachine Learning in Bioinformaticsvaccines and immunoinformatics approaches
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