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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.
Affiliation
  • Carenzo A; Molecular Mechanisms Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan 20133, Italy.
  • Pistore F; Head and Neck Cancer Medical Oncology 3 Department, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan 20133, Italy.
  • Serafini MS; Molecular Mechanisms Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan 20133, Italy.
  • Lenoci D; Molecular Mechanisms Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan 20133, Italy.
  • Licata AG; Molecular Mechanisms Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan 20133, Italy.
  • De Cecco L; Molecular Mechanisms Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan 20133, Italy.
Bioinformatics ; 38(10): 2940-2942, 2022 05 13.
Article in En | MEDLINE | ID: mdl-35561166
ABSTRACT

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.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Transcriptome / Neoplasms Limits: Humans Language: En Year: 2022 Type: Article

Full text: 1 Database: MEDLINE Main subject: Transcriptome / Neoplasms Limits: Humans Language: En Year: 2022 Type: Article