Cancer Genome Interpreter (CGI) is designed to support the identification of tumor alterations that drive the disease and/or which may be therapeutically actionable. CGI relies on computational methods –In silico saturation mutagenesis of cancer genes (BoostDM and OncodriveMut)– as well as on knowledge collected across the public domain to annotate the alterations in a tumor according to several levels of evidence.

With a list of genomic alterations in a tumor of a given cancer type as input, the CGI automatically recognizes the format, remaps the variants as needed and standardizes the annotation for downstream compatibility. Next, it identifies the likely driver alterations in cancer driver genes in the tumor type in question using computational methods (BoostDM and OncodriveMut).

Moreover, mutations observed in the tumor that are known to be tumorigenic (known oncogenic mutations) are annotated. Alterations that constitute biomarkers of response to anti-cancer drugs are identified according to several databases (CIViC, OncoKB and the Cancer Biomarkers database).

Abel Gonzalez-Perez
Núria López-Bigas

Jordi Deu-Pons
Lenka Segura
Iker Reyes
David Martínez
Carlos López Elorduy

Ferrán Muiños
Francisco Martínez-Jimenez
Santiago González
Santiago Demajo

David Tamborero
Rodrigo Dientsmann
Carlota Rubio-Pérez

Cancer Genome Interpreter aims to benefit the scientific and clinical community. The tool and all associated datasets are available under the Creative Commons Attribution-NonCommercial 4.0 (BY-NC) license. This means you are free to:

Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
Under the following terms:
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