Q (sonnet): What percentage of colorectal cancer samples have KRAS mutations in the MSK-CHORD Study?

▶ read_guide
{
 "uri": "cbioportal://mutation-frequency-guide"
}

▶ read_guide
{
 "uri": "cbioportal://sample-filtering-guide"
}

▶ search_oncotree
{
 "search_term": "colorectal"
}

▶ list_studies
{
 "search": "MSK-CHORD"
}

◀ result
# Mutation Frequency Analysis Guide

## IMPORTANT: Reporting Mutation Frequencies
- **ALWAYS report frequencies as percentages**, not raw counts: `frequency = (altered_samples / total_profiled_samples) × 100`
- For quick frequency lookups, **prefer the TCGA Pan-Cancer Atlas study first**, then offer to expand to other studies
- When reporting across multiple studies, show **ranges** (e.g., "TP53 is mutated in 30–60% of samples") rather than a single average
- **NEVER** sum mutation events across studies to compute an aggregate frequency — this can exceed 100% due to double-counting
- Warn users that samples may overlap across cohorts (e.g., MSK studies may share patients)
- **Choose and state the counting unit**: use patient-level frequencies for prevalence/rate questions unless the user explicitly asks for samples; use sample-level frequencies when the user asks about samples.
- **For "across cancer types" questions**, jump to the [Cross-Cancer-Type Mutation Frequency](#cross-cancer-type-mutation-frequency) section below — there is one correct recipe and several common wrong ones.

## Counting Unit: Samples vs Patients

Before answering any mutation count or frequency question, decide whether the unit is samples or patients and state that choice in the answer.

| User wording | Counting unit |
|--------------|---------------|
| "prevalence", "rate", "fraction of patients", "patients with", "how common is" | Patient-level: `COUNT(DISTINCT patient_unique_id)` |
| "samples", "specimens", "biopsies", sample-level cohort composition | Sample-level: `COUNT(DISTINCT sample_unique_id)` |
| Ambiguous | Ask, or default to patient-level for prevalence/rate language and say so |

### Cross-study sample-count caveat

When an answer touches more than one study and reports a sample count, prepend a one-line caveat:

> Sample IDs are unique within cBioPortal study prefixes, not guaranteed biological-sample identifiers across studies; overlapping cohorts can count the same patient/sample more than once.

Prefer one of these safer approaches:

- Use a shipped `cancer_study_query_preferences` cohort such as `pan_cancer_tcga` or `all_studies_non_redundant`.
- Restrict to one named study.
- Aggregate by `patient_unique_id` when the biological question is patient prevalence.

## STOP rule: a frequency above 100% means your query is wrong

If your query returns a frequency over 100%, **do not try to debug or explain the data inconsistency to the user**. The cause is always one of these query bugs:

- Summing mutation events instead of `COUNT(DISTINCT sample_unique_id)` for the numerator
- Using a study-wide sample count as the denominator instead of the gene-specific profiled count
- Cross-study aggregation where the same biological sample appears under multiple `sample_unique_id` values (e.g., MSK-IMPACT and MSK-CHORD share patients)
- **Joining the profiled CTE through `gene_panel` / `gene_panel_list` without a WES branch.** `gene_panel_id = 'WES'` is *not* a row in … (36467 more chars)

◀ result
# Sample and Study Filtering Guide

## Overview
Proper filtering is essential for meaningful cBioPortal analysis. This guide covers filtering by studies, sample types, and other criteria.

## Study-Level Filtering

### 1. Always Filter by Study
Every query should specify a study to ensure consistent results:

```sql
-- Always include study filtering
SELECT *
FROM your_table
WHERE
    cancer_study_identifier = 'your_study_id'
    -- Additional filters...
```

### 2. Find Available Studies

```sql
-- Discover available studies
SELECT
    cancer_study_identifier,
    name,
    description,
    type_of_cancer_id
FROM cancer_study
ORDER BY cancer_study_identifier;
```

### 3. Study Information

```sql
-- Get detailed study information
SELECT
    cs.cancer_study_identifier,
    cs.name as study_name,
    cs.description,
    cs.sample_count,
    COUNT(DISTINCT p.internal_id) as patient_count
FROM cancer_study cs
LEFT JOIN patient p ON cs.cancer_study_id = p.cancer_study_id
WHERE
    cs.cancer_study_identifier = 'your_study_id'
GROUP BY cs.cancer_study_identifier, cs.name, cs.description, cs.sample_count;
```

### 4. Find Studies by Available Data Types

Use this when the user asks *"which studies have mutation and copy-number data for X"*, *"studies with expression for Y"*, *"is there any imaging data"*, or any *"studies with Z data"* question. `cancer_study` has one precomputed sample count per data type — filter on them. No join and no schema exploration needed. These are the same counts as the portal's study list and its "Data type" filter.

**Canonical query — studies with ALL requested data types for a cancer type:**

```sql
SELECT
    cancer_study_identifier,
    name,
    sample_count,
    mutation_sample_count,
    cna_sample_count
FROM cancer_study
WHERE type_of_cancer_id = 'luad'          -- ← OncoTree code from search_oncotree
  AND mutation_sample_count > 0           -- ← one condition per required data type
  AND cna_sample_count > 0
ORDER BY sample_count DESC;
```

**Data type → column** (a count of 0 means the study doesn't have that data):

| Data type in the user's question | Column (portal "Data type" filter label) |
|---|---|
| samples in the study | `sample_count` |
| mutation / mutations | `mutation_sample_count` ("Mutations") |
| copy-number / CNA / amplification / deletion | `cna_sample_count` ("CNA") |
| structural variant / fusion | `structural_variant_sample_count` |
| RNA / mRNA / gene expression (any platform) | `mrna_expression_sample_count` — use this for "which studies have expression data" |
| specifically the portal's "RNA-Seq" filter | `rna_seq_sample_count` ("RNA-Seq") — counts only the `<study>_rna_seq_v2_mrna` list; 0 for many GDC and iAtlas studies that do have RNA-Seq |
| specifically the portal's "RNA (microarray)" filter | `mrna_microarray_sample_count` ("RNA (microarray)") — counts only the `<study>_mrna` list |
| microRNA | `mirna_sample_count` ("miRNA") |
| protein / RPPA | `rppa_sample_count` ("RPPA") |
| mas … (7866 more chars)

◀ result
{"result":[{"code":"COADREAD","name":"Colorectal Adenocarcinoma","score":60,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD"},{"code":"CAIS","name":"Colon Adenocarcinoma In Situ","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > CAIS"},{"code":"CMC","name":"Medullary Carcinoma of the Colon","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > CMC"},{"code":"COAD","name":"Colon Adenocarcinoma","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > COAD"},{"code":"MACR","name":"Mucinous Adenocarcinoma of the Colon and Rectum","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > MACR"},{"code":"READ","name":"Rectal Adenocarcinoma","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > READ"},{"code":"SRCCR","name":"Signet Ring Cell Adenocarcinoma of the Colon and Rectum","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > SRCCR"}]}

◀ result
{"result":[{"cancer_study_identifier":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","type_of_cancer_id":"mixed","sample_count":25040,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=msk_chord_2024"}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH cohort AS (
    SELECT DISTINCT sample_unique_id
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'msk_chord_2024'
      AND attribute_name = 'CANCER_TYPE'
      AND attribute_value = 'Colorectal Cancer'
),
altered AS (
    SELECT COUNT(DISTINCT sample_unique_id) AS altered_samples
    FROM genomic_event_derived
    WHERE cancer_study_identifier = 'msk_chord_2024'
      AND variant_type = 'mutation'
      AND mutation_status != 'UNCALLED'
      AND hugo_gene_symbol = 'KRAS'
      AND off_panel = 0
      AND sample_unique_id IN (SELECT sample_unique_id FROM cohort)
),
profiled_for_gene AS (
    SELECT sample_unique_id, cancer_study_identifier
    FROM mutation_panel_gene_coverage
    WHERE hugo_gene_symbol = 'KRAS'
      AND cancer_study_identifier = 'msk_chord_2024'
    UNION ALL
    SELECT sample_unique_id, cancer_study_identifier
    FROM mutation_wes_coverage
    WHERE cancer_study_identifier = 'msk_chord_2024'
),
profiled AS (
    SELECT COUNT(DISTINCT sample_unique_id) AS profiled_samples
    FROM profiled_for_gene
    WHERE sample_unique_id IN (SELECT sample_unique_id FROM cohort)
)
SELECT altered_samples, profiled_samples,
       ROUND(altered_samples * 100.0 / profiled_samples, 1) AS frequency_pct
FROM altered, profiled;
"
}

◀ result
{"rows":[{"altered_samples":2355,"profiled_samples":5543,"frequency_pct":42.5}]}

▶ resolve_and_route
{
 "studyIds": [
  "msk_chord_2024"
 ]
}

◀ result
{"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","sampleCount":25040,"studyViewUrl":"https://www.cbioportal.org/study?id=msk_chord_2024","metadata":{"clinicalAttributeIds":["ADRENAL_GLANDS","BONE","CANCER_TYPE","CANCER_TYPE_DETAILED","CLINICAL_GROUP","CLINICAL_SUMMARY","CNS_BRAIN","CURRENT_AGE_DEID","DIAGNOSIS_DESCRIPTION","ETHNICITY","FRACTION_GENOME_ALTERED","GENDER","GENE_PANEL","GLEASON_FIRST_REPORTED","GLEASON_HIGHEST_REPORTED","GLEASON_SAMPLE_LEVEL","HER2","HISTORY_OF_PDL1","HR","ICD_O_HISTOLOGY_DESCRIPTION","INTRA_ABDOMINAL","LIVER","LUNG","LYMPH_NODES","METASTATIC_SITE","MSI_COMMENT","MSI_SCORE","MSI_TYPE","MUTATION_COUNT","NUM_ICDO_DX","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","OTHER","PATHOLOGICAL_GROUP","PDL1_POSITIVE","PLEURA","PRIMARY_SITE","PRIOR_MED_TO_MSK","RACE","REPRODUCTIVE_ORGANS","SAMPLE_CLASS","SAMPLE_COUNT","SAMPLE_COVERAGE","SAMPLE_TYPE","SMOKING_PREDICTIONS_3_CLASSES","SOMATIC_STATUS","STAGE_HIGHEST_RECORDED","TMB_NONSYNONYMOUS","TUMOR_PURITY"],"molecularProfileIds":["msk_chord_2024_cna","msk_chord_2024_mutations","msk_chord_2024_structural_variants"],"availableComparisonTabs":["overlap","clinical","survival","alterations","mutations"]}}]}}

▶ navigate_to_study_view
{
 "studyIds": [
  "msk_chord_2024"
 ],
 "filterJson": {
  "clinicalDataFilters": [
   {
    "attributeId": "CANCER_TYPE",
    "values": [
     {
      "value": "Colorectal Cancer"
     }
    ]
   }
  ],
  "geneFilters": [
   {
    "molecularProfileIds": [
     "msk_chord_2024_mutations"
    ],
    "geneQueries": [
     [
      {
       "hugoGeneSymbol": "KRAS"
      }
     ]
    ]
   }
  ]
 }
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/study/summary?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Colorectal%20Cancer%22%7D%5D%7D%5D%2C%22geneFilters%22%3A%5B%7B%22geneQueries%22%3A%5B%5B%7B%22hugoGeneSymbol%22%3A%22KRAS%22%7D%5D%5D%2C%22molecularProfileIds%22%3A%5B%22msk_chord_2024_mutations%22%5D%7D%5D%7D","url":"https://www.cbioportal.org/study/summary?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Colorectal%20Cancer%22%7D%5D%7D%5D%2C%22geneFilters%22%3A%5B%7B%22geneQueries%22%3A%5B%5B%7B%22hugoGeneSymbol%22%3A%22KRAS%22%7D%5D%5D%2C%22molecularProfileIds%22%3A%5B%22msk_chord_2024_mutations%22%5D%7D%5D%7D","data":{"studyIds":["msk_chord_2024"],"studies":[{"studyId":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","sampleCount":25040}],"tab":"summary","hasFilters":true,"hasPlotsConfig":false,"pageDescription":"Overview of all study data displayed as interactive charts summarizing available clinical and genomic data. Click within a chart to filter. Additional charts may be available in the Charts menu."}}

▶ navigate_to_results_view
{
 "studyIds": [
  "msk_chord_2024"
 ],
 "genes": [
  "KRAS: MUT"
 ],
 "tab": "oncoprint",
 "studyViewFilter": {
  "clinicalDataFilters": [
   {
    "attributeId": "CANCER_TYPE",
    "values": [
     {
      "value": "Colorectal Cancer"
     }
    ]
   }
  ]
 }
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/oncoprint?session_id=6ab7f466e497aad53593c5a0","url":"https://www.cbioportal.org/results/oncoprint?session_id=6ab7f466e497aad53593c5a0","data":{"studyIds":["msk_chord_2024"],"studies":[{"studyId":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","sampleCount":25040}],"genes":["KRAS"],"filteredSampleCount":5543,"caseSetId":"-1","sessionId":"6ab7f466e497aad53593c5a0","studyViewUrl":"https://www.cbioportal.org/study?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Colorectal%20Cancer%22%7D%5D%7D%5D%7D","pageDescription":"Visual summary of alterations in queried genes across samples."}}

═ answer (success)
## KRAS mutation frequency in colorectal cancer — MSK-CHORD

**2,355 / 5,543 colorectal cancer samples (42.5%)** in the [MSK-CHORD study](https://www.cbioportal.org/study/summary?id=msk_chord_2024) carry a KRAS mutation.

- **Counting unit:** samples (5,543 samples labeled "Colorectal Cancer" in this study)
- **Denominator:** samples actually profiled for KRAS mutations within the colorectal cohort (panel-aware, includes on-panel targeted-sequencing and WES coverage), not the full study-wide sample count
- These are all KRAS mutation types combined (no filtering for specific hotspots or driver annotation — MSK-CHORD does not carry OncoKB/driver flags in the underlying data)

### Explore further
- [Study View: Colorectal Cancer samples filtered by KRAS mutation](https://www.cbioportal.org/study/summary?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Colorectal%20Cancer%22%7D%5D%7D%5D%2C%22geneFilters%22%3A%5B%7B%22geneQueries%22%3A%5B%5B%7B%22hugoGeneSymbol%22%3A%22KRAS%22%7D%5D%5D%2C%22molecularProfileIds%22%3A%5B%22msk_chord_2024_mutations%22%5D%7D%5D%7D) — cohort overview with clinical/genomic charts
- [OncoPrint: KRAS mutations in the colorectal cancer subset](https://www.cbioportal.org/results/oncoprint?session_id=6ab7f466e497aad53593c5a0) — sample-by-sample mutation view (5,543 samples in this filtered cohort)