Is it possible to perform pan-cancer analysis?

Yes, the skill includes logic to iterate through multiple study IDs to compare mutation frequencies of a gene across different cancer types.

What type of molecular data is available?

The skill supports querying mutations, GISTIC copy number alterations, mRNA expression, protein levels (RPPA), and structural variants.

Can I use this for survival analysis?

Yes, the skill provides workflows to fetch clinical attributes like OS_STATUS and OS_MONTHS alongside genomic data for survival correlation and analysis.

Which cancer datasets are accessible?

You can access data from The Cancer Genome Atlas (TCGA), AACR Project GENIE, MSK-IMPACT, and hundreds of other published studies hosted on cBioPortal.

Does this skill require an API key?

No, cBioPortal's public API does not require an API key for accessing its hosted cancer studies.

cBioPortal Cancer Genomics Query

Name: cBioPortal Cancer Genomics Query
Author: henriquescastilho

byhenriquescastilho

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Data Science & ML

Accesses and analyzes multidimensional cancer genomics data from cBioPortal to validate oncogenes and perform survival analysis.

The cbioportal-database skill enables seamless integration with the cBioPortal for Cancer Genomics, an open-access resource containing data from TCGA, AACR Project GENIE, and MSK-IMPACT. It allows researchers and developers to query somatic mutations, copy number alterations (CNA), mRNA expression, and clinical patient data through a standardized REST API. This tool is essential for clinical-genomic profiling, cross-study comparisons, and identifying co-mutation patterns across thousands of tumor samples, providing actionable insights for cancer target validation and bioinformatics workflows directly within Claude.

Key Features

01Retrieve patient-level clinical data and survival statistics

02Query somatic mutation and copy number alteration (CNA) data

03Access molecular profiles for mRNA and protein expression data

041 GitHub stars

05Compute alteration frequencies for specific genes and OncoPrint profiles

06Browse and filter over 500 cancer studies including TCGA and GENIE

Use Cases

01Performing survival analysis to correlate genomic alterations with patient outcomes

02Identifying mutually exclusive or co-occurring mutation patterns in oncogenes

03Validating the mutation frequency of a specific gene across different cancer types

Key Features

01Retrieve patient-level clinical data and survival statistics

02Query somatic mutation and copy number alteration (CNA) data

03Access molecular profiles for mRNA and protein expression data

041 GitHub stars

05Compute alteration frequencies for specific genes and OncoPrint profiles

06Browse and filter over 500 cancer studies including TCGA and GENIE

Use Cases

01Performing survival analysis to correlate genomic alterations with patient outcomes

02Identifying mutually exclusive or co-occurring mutation patterns in oncogenes

03Validating the mutation frequency of a specific gene across different cancer types