{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T21:32:34Z","timestamp":1775079154286,"version":"3.50.1"},"reference-count":11,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2020,3,31]],"date-time":"2020-03-31T00:00:00Z","timestamp":1585612800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"CINECA"},{"name":"ISCRA","award":["HP10CPQJBV"],"award-info":[{"award-number":["HP10CPQJBV"]}]},{"name":"ISCRA","award":["HP10CC5F89"],"award-info":[{"award-number":["HP10CC5F89"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,6,1]]},"abstract":"Abstract<\/jats:title>\n \n Motivation<\/jats:title>\n Gene network inference and master regulator analysis (MRA) have been widely adopted to define specific transcriptional perturbations from gene expression signatures. Several tools exist to perform such analyses but most require a computer cluster or large amounts of RAM to be executed.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n We developed corto, a fast and lightweight R package to infer gene networks and perform MRA from gene expression data, with optional corrections for copy-number variations and able to run on signatures generated from RNA-Seq or ATAC-Seq data. We extensively benchmarked it to infer context-specific gene networks in 39 human tumor and 27 normal tissue datasets.<\/jats:p>\n <\/jats:sec>\n \n Availability and implementation<\/jats:title>\n Cross-platform and multi-threaded R package on CRAN (stable version) https:\/\/cran.r-project.org\/package=corto and Github (development release) https:\/\/github.com\/federicogiorgi\/corto.<\/jats:p>\n <\/jats:sec>\n \n Supplementary information<\/jats:title>\n Supplementary data are available at Bioinformatics online.<\/jats:p>\n <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa223","type":"journal-article","created":{"date-parts":[[2020,3,26]],"date-time":"2020-03-26T16:14:29Z","timestamp":1585239269000},"page":"3916-3917","source":"Crossref","is-referenced-by-count":75,"title":["corto<\/i>\n : a lightweight R package for gene network inference and master regulator analysis"],"prefix":"10.1093","volume":"36","author":[{"given":"Daniele","family":"Mercatelli","sequence":"first","affiliation":[{"name":"Department of Pharmacy and Biotechnology , University of Bologna, Bologna 40126, Italy"}]},{"given":"Gonzalo","family":"Lopez-Garcia","sequence":"additional","affiliation":[{"name":"Genetics and Genomics Science Department , Ichan School of Medicine at Mount Sinai, New York City, NY 10029-5674, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7325-9908","authenticated-orcid":false,"given":"Federico M","family":"Giorgi","sequence":"additional","affiliation":[{"name":"Department of Pharmacy and Biotechnology , University of Bologna, Bologna 40126, Italy"}]}],"member":"286","published-online":{"date-parts":[[2020,3,31]]},"reference":[{"key":"2023063011474099300_btaa223-B1","doi-asserted-by":"crossref","first-page":"838","DOI":"10.1038\/ng.3593","article-title":"Functional characterization of somatic mutations in cancer using network-based inference of protein activity","volume":"48","author":"Alvarez","year":"2016","journal-title":"Nat. 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