OncodriveFML

DOI

Method to identify genomic regions, both coding and non-coding, bearing mutations with significant shift towards high functional impact across a cohort of tumos (FMbias), which are candidates to function as cancer drivers, through a local test.

Software: Python3+

Identifier
DOI https://doi.org/10.34810/data409
Related Identifier IsCitedBy http://bitbucket.org/bbglab/oncodrivefml
Metadata Access https://dataverse.csuc.cat/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34810/data409
Provenance
Creator Mularoni, Loris ORCID logo; Sabarinathan, Radhakrishnan ORCID logo; González-Pérez, Abel ORCID logo; López Bigas, Núria ORCID logo; Déu Pons, Jordi ORCID logo
Publisher CORA.Repositori de Dades de Recerca
Publication Year 2023
Rights Custom Dataset Terms; info:eu-repo/semantics/openAccess; https://dataverse.csuc.cat/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.34810/data409
OpenAccess true
Representation
Resource Type Aggregate data; Dataset
Format text/x-python; application/x-xz; application/gzip; application/octet-stream; text/plain; charset=UTF-8; text/plain; text/plain; charset=US-ASCII; application/x-sh
Size 8192; 3261; 952408; 2286; 655; 571200; 269; 21; 0; 980; 1507; 10413; 7148; 1056; 266; 2888; 743; 45715; 52; 7110; 59; 5654; 39; 1139; 7405; 1308; 17825; 687
Version 1.0
Discipline Life Sciences; Medicine