Q (haiku): what's the best way to put clinical data into cbioportal?

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# cBioPortal FAQ Guide

Curated answers to frequently asked general questions about cBioPortal. Source: [cBioPortal FAQ](https://docs.cbioportal.org/user-guide/faq/).

## What is cBioPortal?

cBioPortal for Cancer Genomics is an open-access, open-source resource for interactive exploration of multidimensional cancer genomics data sets. It was originally developed at Memorial Sloan Kettering Cancer Center (MSK) and is now maintained by a multi-institutional team.

## History

- **2008**: cBioPortal first became available online.
- **2012**: First major publication — Cerami et al., *Cancer Discovery*.
- **2013**: Second major publication — Gao et al., *Science Signaling*.
- **2023**: Third major publication — de Bruijn et al., *Cancer Research*.

## How to Cite cBioPortal

When using cBioPortal in publications, cite these three papers:

1. Cerami et al. "The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data." *Cancer Discovery* 2, 401–404 (2012). doi:10.1158/2159-8290.CD-12-0095
2. Gao et al. "Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal." *Science Signaling* 6, pl1 (2013). doi:10.1126/scisignal.2004088
3. de Bruijn et al. "Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal." *Cancer Research* 83, 3861–3867 (2023). doi:10.1158/0008-5472.CAN-23-0816

Also cite the specific study publication(s) whose data you used.

## What Data Types Does cBioPortal Contain?

- **Mutations** (non-synonymous somatic mutations)
- **DNA copy-number alterations** (CNA) from GISTIC or other methods
- **mRNA expression** data (RNA-seq, microarray)
- **Protein/phosphoprotein** levels (RPPA, mass spectrometry)
- **DNA methylation** data
- **Structural variants** (gene fusions, rearrangements)
- **Clinical data** (demographics, diagnosis, treatment, outcomes)

Note: Synonymous mutations are not included in cBioPortal.

## What Cancer Types Are in the Database?

Answer from the studies actually loaded, not from the OncoTree ontology (OncoTree lists hundreds of codes, most with no study here). One query:

```sql
SELECT tc.type_of_cancer_id, tc.name, tc.tissue, count() AS studies
FROM cancer_study cs
JOIN type_of_cancer tc ON cs.type_of_cancer_id = tc.type_of_cancer_id
GROUP BY tc.type_of_cancer_id, tc.name, tc.tissue
ORDER BY studies DESC;
```

Report how many distinct cancer types there are across how many studies, grouped by `tissue`. `mixed` ("Mixed Cancer Types") marks multi-cancer studies such as MSK-IMPACT and MSK-CHORD; their per-sample cancer types are in `clinical_data_derived` (`CANCER_TYPE`).

## Data Types Usually Not Stored Directly

cBioPortal generally does not store:

- raw CT, MRI, pathology-slide, or histology image files
- raw sequencing files such as BAM, CRAM, or FASTQ
- polygenic risk scores as a standard data type
- full external clinical-trial databases

However, this deployment … (7371 more chars)

═ answer (success)
Based on the guide, here's the best way to put clinical data into cBioPortal:

## Before You Start

First, clarify your goal—are you trying to:

1. **Submit data to the public cBioPortal** — follow the official data curation process
2. **Run or populate a private cBioPortal instance** — use the standard study package formats
3. **Visualize your own data quickly** — use standalone tools

## Official Submission Process

For the **public cBioPortal**, follow these steps:

1. **Prepare your data** using the cBioPortal datahub formats:
   - **Clinical data file** — tab-delimited, with required columns for patient and sample identifiers, plus your clinical attributes (age, sex, tumor grade, treatment, outcomes, etc.)
   - **Sample metadata** — links samples to patients
   - **Molecular data files** — mutations, copy number, expression (if applicable)
   - **Study metadata** — study name, description, cancer type, publication info

2. **Follow cBioPortal data standards:**
   - Use consistent identifiers for patients and samples
   - Format dates and numerical values consistently (the guide notes that `AGE` may be floored for de-identification)
   - Empty clinical values should be handled per cBioPortal conventions
   - Specify your reference genome (hg19/GRCh37 vs. hg38/GRCh38)

3. **Submit through the cBioPortal curation pipeline:**
   - Contact the cBioPortal team at the official documentation site: [cBioPortal Data Format Guide](https://docs.cbioportal.org/)
   - Provide study metadata, clinical files, and molecular data in the standardized formats

## Private Instance

If you're running your own cBioPortal instance, create a **study package** with:
- Clinical and sample metadata files (TSV format)
- Molecular profile files (if applicable)
- Study metadata configuration (XML or JSON)

## Quick Visualization Without Full Submission

For rapid prototyping without full cBioPortal setup:
- Use **cBioPortal standalone tools** like Mutation Mapper or OncoPrint for visualizing subsets
- Export your processed data to CSV and load into R/Python for custom analysis

**I'd recommend starting with the [cBioPortal documentation](https://docs.cbioportal.org/) on data formats—they have detailed templates for clinical data, file naming conventions, and validation scripts to ensure your data meets requirements before submission.**

Is this for a public submission, or are you running a private instance?