G
Gad Getz
Researcher at Broad Institute
Publications - 627
Citations - 309042
Gad Getz is an academic researcher from Broad Institute. The author has contributed to research in topics: Cancer & Biology. The author has an hindex of 189, co-authored 520 publications receiving 247560 citations. Previous affiliations of Gad Getz include University of Colorado Denver & University of California, San Diego.
Papers
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Journal ArticleDOI
Paralog knockout profiling identifies DUSP4 and DUSP6 as a digenic dependence in MAPK pathway-driven cancers.
Takahiro Ito,Michael J. Young,Ruitong Li,Sidharth S. Jain,Andreas Wernitznig,Andreas Wernitznig,John M. Krill-Burger,Christopher T. Lemke,Davide Monducci,Diego J. Rodriguez,Liang Chang,Liang Chang,Sanjukta Dutta,Debjani Pal,Debjani Pal,Brenton R. Paolella,Michael V. Rothberg,David E. Root,Cory M. Johannessen,Cory M. Johannessen,Laxmi Parida,Gad Getz,Gad Getz,Francisca Vazquez,John G. Doench,Mahdi Zamanighomi,William R. Sellers,William R. Sellers +27 more
TL;DR: In this article, the authors developed a CRISPR paralog targeting library to investigate the viability effects of disrupting 3,284 genes, 5,065 paralog pairs and 815 paralog families.
Journal ArticleDOI
Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples.
Matthew H. Bailey,William Meyerson,L. J. Dursi,Liang-Bo Wang,Guanlan Dong,Wen-Wei Liang,Amila Weerasinghe,Shantao Li,Yize Li,Sean Kelso,Gordon Saksena,Kyle Ellrott,Michael C. Wendl,David A. Wheeler,Gad Getz,Jared T. Simpson,Jared T. Simpson,Mark Gerstein,Li Ding +18 more
TL;DR: This analysis highlights technological divergences between two reproducible somatic variant detection efforts as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium.
Journal ArticleDOI
RNA-SeQC 2: Efficient RNA-seq quality control and quantification for large cohorts.
TL;DR: RNA-SeQC 2 as discussed by the authors is an efficient re-implementation of RNASeqC that adds multiple metrics designed to characterize sample quality across a wide range of RNA-seq protocols.
Posted ContentDOI
Pathway and network analysis of more than 2,500 whole cancer genomes
Matthew A. Reyna,D. Haan,Marta Paczkowska,Lieven Verbeke,Miguel Vazquez,Miguel Vazquez,Abdullah Kahraman,Abdullah Kahraman,S. Pulido Tamayo,Jonathan Barenboim,Lina Wadi,Priyanka Dhingra,Raunak Shrestha,Gad Getz,Michael S. Lawrence,Michael S. Lawrence,Jakob Skou Pedersen,Jakob Skou Pedersen,Mark A. Rubin,David A. Wheeler,Søren Brunak,Søren Brunak,Jose M. G. Izarzugaza,Jose M. G. Izarzugaza,Ekta Khurana,Kathleen Marchal,C. von Mering,Sahinalp Sc,Sahinalp Sc,Alfonso Valencia,Jueri Reimand,Jueri Reimand,Joshua M. Stuart,Benjamin J. Raphael,Pcawg Drivers,Icgc +35 more
TL;DR: Multi-faceted pathway and network analyses of non-coding mutations across 2,583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-Coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.
Patent
Markers associated with chronic lymphocytic leukemia prognosis and progression
Catherine J. Wu,Gad Getz +1 more
TL;DR: In this article, the authors provide methods and devices related to markers (or biomarkers) associated with chronic lymphocytic leukemia (CLL) Examples of these markers include drivers of CLL progression, and utilize this information in predicting disease progression, need, timing and/or nature of treatment regimen, and likelihood and frequency of relapse.