• Medientyp: E-Artikel
  • Titel: hacksig: a unified and tidy R framework to easily compute gene expression signature scores
  • Beteiligte: Carenzo, Andrea; Pistore, Federico; Serafini, Mara S; Lenoci, Deborah; Licata, Armando G; De Cecco, Loris
  • Erschienen: Oxford University Press (OUP), 2022
  • Erschienen in: Bioinformatics
  • Sprache: Englisch
  • DOI: 10.1093/bioinformatics/btac161
  • ISSN: 1367-4803; 1367-4811
  • Schlagwörter: Computational Mathematics ; Computational Theory and Mathematics ; Computer Science Applications ; Molecular Biology ; Biochemistry ; Statistics and Probability
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:title>Abstract</jats:title> <jats:sec> <jats:title>Summary</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Availability and implementation</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Supplementary information</jats:title> <jats:p>Supplementary data are available at Bioinformatics online.</jats:p> </jats:sec>
  • Zugangsstatus: Freier Zugang