Q (haiku): What is the current and future support for storing and analyzing germline variants in cBioPortal, compared to other alternatives?

▶ read_guide
{
 "uri": "cbioportal://germline-guide"
}

◀ result
Germline Variant Guide
======================

Overview
--------
cBioPortal stores both somatic AND germline variant data. Many cBioPortal features work identically for both variant types. This guide explains how to query germline variants and what to be aware of.

How Germline Data is Stored
---------------------------

### mutation_status is free text — always compare case-insensitively
Each study loads its own spelling. Germline calls appear as `'Germline'`, `'GERMLINE'` and `'germline'`; somatic calls as `'Somatic'`, `'SOMATIC'` and `'somatic'`; unannotated mutations as `'NA'`, `'.'`, `'Unknown'`, `'UNKNOWN'`, `'__UNKNOWN__'` and others. Matching one spelling silently drops whole studies (`mutation_status = 'Germline'` misses `all_stjude_2013`, `aml_stjude_2024` and `pog570_bcgsc_2020`).

- **Germline:** `upper(mutation_status) = 'GERMLINE'`
- **Somatic:** `upper(mutation_status) = 'SOMATIC'` — but only when the user asks for somatic-only. Many studies label their somatic calls `'NA'` or `'UNKNOWN'`, so for ordinary mutation questions follow common-pitfalls #3 and exclude only `'UNCALLED'`.
- When unsure, list the values first: `SELECT mutation_status, count() FROM genomic_event_derived WHERE cancer_study_identifier = '{study_id}' AND variant_type = 'mutation' GROUP BY mutation_status`

### Where the column lives
- `genomic_event_derived.mutation_status` (preferred): mutations, and structural variants (from `sv_status`: `'SOMATIC'`, `'Somatic'`, `'GERMLINE'`)
- `mutation_derived.mutationStatus`: the same values for mutations

Identifying Studies with Germline Data
--------------------------------------
Not all studies include germline data. Always check before querying:

```sql
-- Find studies containing germline mutations
SELECT cancer_study_identifier, COUNT(*) as germline_count
FROM genomic_event_derived
WHERE variant_type = 'mutation'
  AND upper(mutation_status) = 'GERMLINE'
GROUP BY cancer_study_identifier
ORDER BY germline_count DESC
```

Common Query Patterns
---------------------

### Count germline vs somatic mutations per gene in a study
```sql
SELECT hugo_gene_symbol, upper(mutation_status) AS status, COUNT(*) as count
FROM genomic_event_derived
WHERE cancer_study_identifier = '{study_id}'
  AND variant_type = 'mutation'
  AND upper(mutation_status) IN ('GERMLINE', 'SOMATIC')
GROUP BY hugo_gene_symbol, status
ORDER BY count DESC
LIMIT 20
```

### Find patients with germline mutations in a specific gene
```sql
SELECT DISTINCT patient_unique_id, sample_unique_id, mutation_variant, mutation_type
FROM genomic_event_derived
WHERE hugo_gene_symbol = '{GENE}'
  AND upper(mutation_status) = 'GERMLINE'
  AND cancer_study_identifier = '{study_id}'
  AND variant_type = 'mutation'
```

### Germline mutation frequency
The numerator is samples with a germline mutation in the gene; the denominator is samples **profiled** for the gene — not samples that happen to have a mutation in it. Take the denominator from mutation-frequency-guide Step 2 (or … (2222 more chars)

▶ read_guide
{
 "uri": "cbioportal://faq-guide"
}

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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.

## 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 may contain links to external viewers or portals through `resource_*` tables. For imaging, pathology, Minerva, HTAN, or viewer questions, read `cbioportal://external-resources-guide` and check those tables before saying the data is absent.

## What the MCP Agent Can and Cannot Produce

The MCP agent can:

- query cBioPortal data and return tables in text/JSON/Markdown
- summarize counts, frequencies, and available attributes
- provide cBioPortal study links and DataHub download links when applicable
- provide SQL snippets or handoff instructions for R/Python/cBioPortal tools

The MCP agent should not promise to:

- render Kaplan-Meier plots or other visual figures directly
- export large … (6558 more chars)

═ answer (success)
Based on the cBioPortal documentation, here's what you need to know about germline variant support:

## Current Support for Germline Variants in cBioPortal

### What cBioPortal Offers
cBioPortal **does support germline variant storage and analysis**. Key capabilities include:

- **Storage:** Both somatic and germline variants coexist in the `genomic_event_derived` and `mutation_derived` tables, identified via the `mutation_status` field
- **Query & Analysis:** Standard cBioPortal features work for germline data:
  - Germline mutation frequency calculations
  - Protein domain analysis and visualization
  - Co-occurrence/co-mutation analysis (with proper filtering)
  - Clinical correlation and stratification
  - Gene panel coverage checking
  - Web interface visualization (OncoPrint, mutations tab, etc.)

### Important Limitations

1. **Sparse Coverage:** Not all studies include germline data. Many studies filter out germline variants during data processing.

2. **Annotation Differences:** 
   - Driver annotations (`driver_filter`, `driver_tiers_filter`) are typically **somatic-only**
   - OncoKB annotations are designed primarily for somatic variants
   - ACMG variant classification (pathogenic, likely pathogenic, VUS) is **not stored** in standard cBioPortal columns

3. **Mutation Status Inconsistency:** Studies use different spellings (`'Germline'`, `'GERMLINE'`, `'germline'`), requiring case-insensitive matching in queries

4. **No Native Pathogenicity Scoring:** cBioPortal does not directly store ACMG or ClinVar pathogenicity classifications

## Comparison to Other Alternatives

| Aspect | cBioPortal | GDC / ClinVar / Other Specialized DBs |
|--------|-----------|----------------------------------|
| **Interactive visualization** | ✓ Strong (OncoPrint, plots, clinical correlation) | Limited; more download-focused |
| **Germline-somatic distinction** | ✓ Supported but sparse across studies | ✓ More comprehensive germline coverage (ClinVar, HGMD) |
| **Pathogenicity annotation** | ✗ Not stored natively | ✓ ACMG, ClinVar, HGMD, OncoKB (somatic) |
| **Raw sequencing files** | ✗ Not available | ✓ GDC provides BAM, CRAM, FASTQ |
| **Clinical data linkage** | ✓ Excellent for studies with rich phenotypes | Varies |
| **Variants of Uncertain Significance (VUS)** | May be present but unclassified | ✓ Explicitly categorized |

## Future Support

The guide notes that **germline studies can be submitted to cBioPortal** using standard datahub formats. The platform is designed to grow as studies include more germline data, but there is **no announced expansion** of pathogenicity annotation features beyond what currently exists.

## Recommendation

**For research use:** cBioPortal excels at exploring germline variant frequencies and clinical correlations within specific studies. **For clinical pathogenicity assessment:** you need specialized databases like ClinVar, HGMD, or OncoKB (for somatic actions) in parallel. **For raw germline variant reanalysis:** use GDC or direct study downloads.

If you're planning to load germline data into cBioPortal, follow the [cBioPortal datahub format documentation](https://docs.cbioportal.org/), and ensure your study package includes mutation_status annotations and clinical metadata aligned with your research questions.