Mariano J Alvarez1, James C Chen2, Andrea Califano1. 1. Department of Systems Biology and. 2. Department of Systems Biology and Department of Dermatology, Columbia University, New York, NY 10032 USA.
Abstract
UNLABELLED: Identification of driver mutations in human diseases is often limited by cohort size and availability of appropriate statistical models. We propose a method for the systematic discovery of genetic alterations that are causal determinants of disease, by prioritizing genes upstream of functional disease drivers, within regulatory networks inferred de novo from experimental data. Here we present the implementation of Driver-gene Inference by Genetical-Genomic Information Theory as an R-system package. AVAILABILITY AND IMPLEMENTATION: The diggit package is freely available under the GPL-2 license from Bioconductor (http://www.bioconductor.org).
UNLABELLED: Identification of driver mutations in human diseases is often limited by cohort size and availability of appropriate statistical models. We propose a method for the systematic discovery of genetic alterations that are causal determinants of disease, by prioritizing genes upstream of functional disease drivers, within regulatory networks inferred de novo from experimental data. Here we present the implementation of Driver-gene Inference by Genetical-Genomic Information Theory as an R-system package. AVAILABILITY AND IMPLEMENTATION: The diggit package is freely available under the GPL-2 license from Bioconductor (http://www.bioconductor.org).
Authors: James C Chen; Mariano J Alvarez; Flaminia Talos; Harshil Dhruv; Gabrielle E Rieckhof; Archana Iyer; Kristin L Diefes; Kenneth Aldape; Michael Berens; Michael M Shen; Andrea Califano Journal: Cell Date: 2014-10-09 Impact factor: 41.582
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Authors: Michael P Menden; Dennis Wang; Mike J Mason; Bence Szalai; Krishna C Bulusu; Yuanfang Guan; Thomas Yu; Jaewoo Kang; Minji Jeon; Russ Wolfinger; Tin Nguyen; Mikhail Zaslavskiy; In Sock Jang; Zara Ghazoui; Mehmet Eren Ahsen; Robert Vogel; Elias Chaibub Neto; Thea Norman; Eric K Y Tang; Mathew J Garnett; Giovanni Y Di Veroli; Stephen Fawell; Gustavo Stolovitzky; Justin Guinney; Jonathan R Dry; Julio Saez-Rodriguez Journal: Nat Commun Date: 2019-06-17 Impact factor: 14.919