Pathway-based expression profiles allow for high-level interpretation of transcriptomic data and systematic comparison of dysregulated cellular programs. We have previously demonstrated the efficacy of pathway-based approaches with two different applications: the drug set enrichment analysis and the Gene2drug analysis. Here, we present a software tool that allows to easily convert gene-based profiles to pathway-based profiles and analyze them within the popular R framework. We also provide pre-computed profiles derived from the original Connectivity Map and its next generation release, i.e. the LINCS database. Availability and implementation: The tool is implemented as the R/Bioconductor package gep2pep and can be freely downloaded from https://bioconductor.org/packages/gep2pep.

gep2pep: A bioconductor package for the creation and analysis of pathway-based expression profiles / Napolitano, F.; Carrella, D.; Gao, X.; di Bernardo, D.. - In: BIOINFORMATICS. - ISSN 1367-4803. - 36:6(2020), pp. 1944-1945. [10.1093/bioinformatics/btz803]

gep2pep: A bioconductor package for the creation and analysis of pathway-based expression profiles

di Bernardo D.
Ultimo
Supervision
2020

Abstract

Pathway-based expression profiles allow for high-level interpretation of transcriptomic data and systematic comparison of dysregulated cellular programs. We have previously demonstrated the efficacy of pathway-based approaches with two different applications: the drug set enrichment analysis and the Gene2drug analysis. Here, we present a software tool that allows to easily convert gene-based profiles to pathway-based profiles and analyze them within the popular R framework. We also provide pre-computed profiles derived from the original Connectivity Map and its next generation release, i.e. the LINCS database. Availability and implementation: The tool is implemented as the R/Bioconductor package gep2pep and can be freely downloaded from https://bioconductor.org/packages/gep2pep.
2020
gep2pep: A bioconductor package for the creation and analysis of pathway-based expression profiles / Napolitano, F.; Carrella, D.; Gao, X.; di Bernardo, D.. - In: BIOINFORMATICS. - ISSN 1367-4803. - 36:6(2020), pp. 1944-1945. [10.1093/bioinformatics/btz803]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/888652
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