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

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...

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Detalles Bibliográficos
Autores principales: Ranathunge, Chathurani, Patel, Sagar S, Pinky, Lubna, Correll, Vanessa L, Chen, Shimin, Semmes, O John, Armstrong, Robert K, Combs, C Donald, Nyalwidhe, Julius O
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Application Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10010602/
https://www.ncbi.nlm.nih.gov/pubmed/36922981
http://dx.doi.org/10.1093/bioadv/vbad025
Descripción
Sumario: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: Supplementary data are available at Bioinformatics Advances online.

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