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hacksig: a unified and tidy R framework to easily compute gene expression signature scores
SUMMARY: Hundreds of gene expression signatures have been developed during the last two decades. However, due to the multitude of development procedures and sometimes a lack of explanation for their implementation, it can become challenging to apply the original method on custom data. Moreover, at p...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9113261/ https://www.ncbi.nlm.nih.gov/pubmed/35561166 http://dx.doi.org/10.1093/bioinformatics/btac161 |
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author | Carenzo, Andrea Pistore, Federico Serafini, Mara S Lenoci, Deborah Licata, Armando G De Cecco, Loris |
author_facet | Carenzo, Andrea Pistore, Federico Serafini, Mara S Lenoci, Deborah Licata, Armando G De Cecco, Loris |
author_sort | Carenzo, Andrea |
collection | PubMed |
description | SUMMARY: Hundreds of gene expression signatures have been developed during the last two decades. However, due to the multitude of development procedures and sometimes a lack of explanation for their implementation, it can become challenging to apply the original method on custom data. Moreover, at present, there is no unified and tidy interface to compute signature scores with different single sample enrichment methods. For these reasons, we developed hacksig, an R package intended as a unified framework to obtain single sample scores with a tidy output as well as a collection of manually curated gene signatures and methods from cancer transcriptomics literature. AVAILABILITY AND IMPLEMENTATION: The hacksig R package is freely available on CRAN (https://CRAN.R-project.org/package=hacksig) under the MIT license. The source code can be found on GitHub at https://github.com/Acare/hacksig. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9113261 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-91132612022-05-18 hacksig: a unified and tidy R framework to easily compute gene expression signature scores Carenzo, Andrea Pistore, Federico Serafini, Mara S Lenoci, Deborah Licata, Armando G De Cecco, Loris Bioinformatics Applications Notes SUMMARY: Hundreds of gene expression signatures have been developed during the last two decades. However, due to the multitude of development procedures and sometimes a lack of explanation for their implementation, it can become challenging to apply the original method on custom data. Moreover, at present, there is no unified and tidy interface to compute signature scores with different single sample enrichment methods. For these reasons, we developed hacksig, an R package intended as a unified framework to obtain single sample scores with a tidy output as well as a collection of manually curated gene signatures and methods from cancer transcriptomics literature. AVAILABILITY AND IMPLEMENTATION: The hacksig R package is freely available on CRAN (https://CRAN.R-project.org/package=hacksig) under the MIT license. The source code can be found on GitHub at https://github.com/Acare/hacksig. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-03-18 /pmc/articles/PMC9113261/ /pubmed/35561166 http://dx.doi.org/10.1093/bioinformatics/btac161 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Carenzo, Andrea Pistore, Federico Serafini, Mara S Lenoci, Deborah Licata, Armando G De Cecco, Loris hacksig: a unified and tidy R framework to easily compute gene expression signature scores |
title | hacksig: a unified and tidy R framework to easily compute gene expression signature scores |
title_full | hacksig: a unified and tidy R framework to easily compute gene expression signature scores |
title_fullStr | hacksig: a unified and tidy R framework to easily compute gene expression signature scores |
title_full_unstemmed | hacksig: a unified and tidy R framework to easily compute gene expression signature scores |
title_short | hacksig: a unified and tidy R framework to easily compute gene expression signature scores |
title_sort | hacksig: a unified and tidy r framework to easily compute gene expression signature scores |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9113261/ https://www.ncbi.nlm.nih.gov/pubmed/35561166 http://dx.doi.org/10.1093/bioinformatics/btac161 |
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