Armando Giuseppe Licata

@istitutotumori.mi.it

Integrated Biology of Rare Tumors
Fondazione IRCCS Istituto Nazionale dei Tumori



           

https://researchid.co/licataarmando

RESEARCH, TEACHING, or OTHER INTERESTS

Oncology

2

Scopus Publications

Scopus Publications

  • Peritoneal fluid COVID-19 testing in patients with a negative nasopharyngeal swab: prospective study
    Armando G Licata, Chiara M Ciniselli, Luca Sorrentino, Arianna Micali, Maria Grazia Daidone, Marcello Guaglio, Manuela Gariboldi, Paolo Verderio, Loris De Cecco, and Maurizio Cosimelli
    Oxford University Press (OUP)
    Molecular Mechanisms Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy Bioinformatics and Biostatistics Unit, Department of Applied Research and Technological Development, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy Colorectal Surgery Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy Scientific Directorate, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy Genetic Epidemiology and Pharmacogenomics Unit Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

  • hacksig: A unified and tidy R framework to easily compute gene expression signature scores
    Andrea Carenzo, Federico Pistore, Mara S Serafini, Deborah Lenoci, Armando G Licata, and Loris De Cecco
    Oxford University Press (OUP)
    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.