GISTIC statistics

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Citations per year

Number of citations per year for the bioinformatics software tool GISTIC

Tool usage distribution map

This map represents all the scientific publications referring to GISTIC per scientific context
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Associated diseases

This word cloud represents GISTIC usage per disease context

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GISTIC specifications


Unique identifier OMICS_02296
Alternative name Genomic Identification of Significant Targets in Cancer
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages MATLAB
Computer skills Advanced
Version 2.0.22
Stability Stable
Maintained Yes


No version available


  • person_outline Gad Getz
  • person_outline Rameen Beroukhim

Publications for Genomic Identification of Significant Targets in Cancer

GISTIC citations


Genomic profiling of dedifferentiated liposarcoma compared to matched well differentiated liposarcoma reveals higher genomic complexity and a common origin

PMCID: 5880260
PMID: 29610390
DOI: 10.1101/mcs.a002386

[…] ta. For assessing amplifications and deletions, log2 scores > 0.5 were considered gains, whereas log2 scores < −0.5 were considered losses. Focal somatic copy-number alterations were identified using GISTIC2.0 () at the 95% confidence level. See Supplemental Methods for comments on somatic copy-number alterations profiles in FFPE samples. Gene-level copy-number assessment was done using customized […]


Genomic analysis of liver cancer unveils novel driver genes and distinct prognostic features

PMCID: 5858179
PMID: 29556353
DOI: 10.7150/thno.22010

[…] Aside from point mutations and short insertions/deletions, we used GISTIC2 to analyze DNA copy number alterations (CNAs) based on segmentation data obtained from TCGA to delineate genome-wide focal DNA gain and loss . Significant arm-level alterations include gain of […]


Genomic analysis of head and neck cancer cases from two high incidence regions

PLoS One
PMCID: 5788352
PMID: 29377909
DOI: 10.1371/journal.pone.0191701

[…] the normalized copy number. Germline copy number alterations were removed using the Database of Genomic Variants []. Identification of significant amplified or deleted regions was performed by using GISTIC 2.0 [] using 99% confidence level and q-value threshold 0.25. Focal amplification or deletion for all the 14 genes sequenced was determined only using the GISTIC copy number value 2 or -2 respe […]


Efficacy of histology agnostic and molecularly driven HER2 inhibitors for refractory cancers

PMCID: 5839398
PMID: 29515767
DOI: 10.18632/oncotarget.24188

[…] y 4 × 180K, Agilent technologies, Palo alto, CA []. The copy number alterations detected with CGHa were classified into 5 categories, namely deletion, loss, neutral, gain and amplification, using the GISTIC algorithm []. Amplifications in GISTIC confirmed by a > ×0.7 log2 ratio with a length less than 10 Mb were considered of interest for the current study. […]


Integrative genomic and transcriptomic analysis of leiomyosarcoma

Nat Commun
PMCID: 5762758
PMID: 29321523
DOI: 10.1038/s41467-017-02602-0

[…] CNA profiles. Segmentation was performed with PSCBS, segmentation files and windows used for CNA estimation were converted to a compound segmentation file and marker files that were used as input for GISTIC2.0, and processing was performed with default parameters. For LMS cell lines, copy numbers were estimated from whole-genome sequencing data using allele-specific copy number estimation from seq […]


CINdex: A Bioconductor Package for Analysis of Chromosome Instability in DNA Copy Number Data

Cancer Inform
PMCID: 5761903
PMID: 29343938
DOI: 10.1177/1176935117746637

[…] ysis of DNA, Circular Binary Segmentation (CBS), and Hidden Markov Model (HMM). Consensus CNV/CNA detection methods can be categorized into 1-stage and 2-stage approaches. A 2-stage approach, such as Genomic Identification of Significant Targets in Cancer (GISTIC), involves a step of copy number change detection in individual profiles and a subsequent statistical analysis of commonly altered DNA r […]

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GISTIC institution(s)
Cancer Program, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA; Department of Cancer Biology, Dana Farber Cancer Institute, Boston, MA, USA; The Center for Cancer Genome Discovery, Dana Farber Cancer Institute, Boston, MA, USA
GISTIC funding source(s)
Supported by a Genome Characterization Center Grant (U24CA143867) awarded as part of the NCI/NHGRI funded Cancer Genome Atlas (TCGA) project; by Medical Scientist Training Program (MSTP) Award Number T32GM07753 from the National Institute of General Medical Sciences; by NIH K08CA122833, a V Foundation Scholarship, and the Doris Duke Charitable Foundation.

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