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GeneSelectR
View on CRAN: Click
here
Download and install GeneSelectR package within the R console
Install from CRAN:
install.packages("GeneSelectR")
Install from Github:
library("remotes")
install_github("cran/GeneSelectR")
Install by package version:
library("remotes")
install_version("GeneSelectR", "1.0.1")
Attach the package and use:
library("GeneSelectR")
Maintained by
Damir Zhakparov
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.GeneSelectR . https://github.com/dzhakparov/GeneSelectR/issues . https://github.com/dzhakparov/GeneSelectR . GeneSelectR results . GeneSelectR.pdf . GeneSelectR_1.0.1.tar.gz . GeneSelectR_1.0.1.zip . GeneSelectR_1.0.1.zip . GeneSelectR_1.0.1.zip . GeneSelectR_1.0.1.tgz . GeneSelectR_1.0.1.tgz . GeneSelectR_1.0.1.tgz . GeneSelectR_1.0.1.tgz . GeneSelectR_1.0.1.tgz . GeneSelectR_1.0.1.tgz . GeneSelectR archive . https://CRAN.R-project.org/package=GeneSelectR .
First Published: 2023-12-13
Latest Update: 2024-02-03
Description:
The workflow is a versatile R package designed for comprehensive feature selection in bulk RNAseq datasets. Its key innovation lies in the seamless integration of the 'Python' 'scikit-learn' () machine learning framework with R-based bioinformatics tools. 'GeneSelectR' performs robust Machine Learning-driven (ML) feature selection while leveraging 'Gene Ontology' (GO) enrichment analysis as described by Thomas PD et al. (2022) , using 'clusterProfiler' (Wu et al., 2021) and semantic similarity analysis powered by 'simplifyEnrichment' (Gu, Huebschmann, 2021) . This combination of methodologies optimizes computational and biological insights for analyzing complex RNAseq datasets.
How to cite:
Damir Zhakparov (2023). GeneSelectR: 'GeneSelectR' - Comprehensive Feature Selection Workflow for Bulk RNAseq Datasets. R package version 1.0.1, https://cran.r-project.org/web/packages/GeneSelectR. Accessed 17 Feb. 2025.
Previous versions and publish date:
1.0.0 (2023-12-13 13:30)
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