GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers

By Craig H. Mermel, S. Schumacher, Barbara A. Hill, Matthew Meyerson, Rameen Beroukhim, Gad Getz. Genome Biology, 2011

3,145 citations recorded by the source corpus.

We describe methods with enhanced power and specificity to identify genes targeted by somatic copy-number alterations (SCNAs) that drive cancer growth. By separating SCNA profiles into underlying arm-level and focal alterations, we improve the estimation of background rates for each category. We additionally describe a probabilistic method for defining the boundaries of selected-for SCNA regions with user-defined confidence. Here we detail this revised computational approach, GISTIC2.0, and validate its performance in real and simulated datasets.

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/232406e0bc86171b8784de7817caed978e23a616

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Citations in the corpus

Molecular and genetic properties of tumors associated with local immune cytolytic activity (2015, neutral): “GISTIC2 (Mermel et al., 2011) gene-level, zero-centered, focal copy number calls for each patient were accessed from GDAC Firehose.”
Integrated Genomic Characterization of Papillary Thyroid Carcinoma (2014, background): “(E) Number and frequency of SCNAs (left), chromosome-sample matrix of SCNAs across the cohort (middle) with focal deletions in BRAF and PTEN (bottom), GISTIC2 significance (right).”
Evolution and impact of subclonal mutations in chronic lymphocytic leukemia (2013, neutral): “0 (Mermel et al., 2011) to 111 matched tumor and normal samples, which were analyzed by SNP6.”
Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma (2017, neutral): “GISTIC analysis of focal amplifications and deletions in the high-purity group revealed a number of recurrent events containing known oncogenic drivers (Figure S1D; Table S3) (Mermel et al., 2011).”
Punctuated Evolution of Prostate Cancer Genomes (2013, neutral): “To this end, we quantified recurrent SCNAs in each genome by counting amplifications and deletions that overlapped with regions of significant SNCAs identified by GISTICv2 analysis (e.g., the TP53 and PTEN loci) across 199 tumors reported here and in a previous study (Barbieri et al., 2012; Mermel e”
Maftools: efficient and comprehensive analysis of somatic variants in cancer (2018, background): “Maftools also provides optionsto integrate and analyze copy number variation (CNV) data generated by programs such as genomic identification of significant targets in cancer (GISTIC) and circular binarysegmentation(CBS)algorithms (Olshenet al.2004; Mermel et al. 2011).”
Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma. (2018, methodology): “GISTIC2.”
Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy (2017, methodology): “For each of 800 genomic regions, corresponding to cytogenetic bands, the corresponding copy number level (average copy number change along the region) at the arm-level or focal-level were considered (using GISTIC2).”
Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas. (2017, neutral): “2.6 Koboldt et al., 2012 RRID:SCR_006849; http://tvap.genome.wustl.edu/ tools/varscan/ Ziggurat Deconstruction Mermel et al., 2011 PMID: 21527027 Other Resource website for TCGA Sarcoma paper This paper https://tcga-data.nci.nih.gov/docs/publications/ sarc_2017/ Firehose, Firebrowse The Broad…”