Q (haiku): show me P135L mutations in $p14^{ARF}$

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

▶ search_oncotree
{
 "search_term": "p14"
}

◀ 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
{"result":[]}

▶ clickhouse_list_tables
{}

◀ result
{"tables":[{"name":"allele_specific_copy_number"},{"name":"alteration_driver_annotation"},{"name":"cancer_study"},{"name":"cancer_study_query_preferences"},{"name":"cancer_study_tags"},{"name":"cbioportal_sequence_state"},{"name":"clinical_attribute_counts"},{"name":"clinical_attribute_meta"},{"name":"clinical_data_derived"},{"name":"clinical_event"},{"name":"clinical_event_data"},{"name":"clinical_event_data_derived"},{"name":"clinical_event_derived"},{"name":"clinical_patient"},{"name":"clinical_sample"},{"name":"cna_event"},{"name":"cna_panel_gene_coverage"},{"name":"cna_wes_coverage"},{"name":"co_altered_genes_in_study"},{"name":"copy_number_seg"},{"name":"copy_number_seg_file"},{"name":"gene"},{"name":"gene_alias"},{"name":"gene_alteration_frequency_by_cancer_type"},{"name":"gene_cna_distribution_in_study"},{"name":"gene_mutation_frequency_by_cancer_type"},{"name":"gene_mutation_frequency_in_studies"},{"name":"gene_mutation_frequency_in_study"},{"name":"gene_mutation_variants_in_study"},{"name":"gene_pair_coexpression"},{"name":"gene_panel"},{"name":"gene_panel_list"},{"name":"gene_panel_to_gene_derived"},{"name":"generic_assay_data_derived"},{"name":"generic_assay_meta_derived"},{"name":"generic_assay_profile_entity_derived"},{"name":"generic_entity_properties"},{"name":"geneset"},{"name":"geneset_gene"},{"name":"geneset_hierarchy_leaf"},{"name":"geneset_hierarchy_node"},{"name":"genetic_alteration"},{"name":"genetic_alteration_derived"},{"name":"genetic_entity"},{"name":"genetic_profile"},{"name":"genetic_profile_link"},{"name":"genetic_profile_samples"},{"name":"genomic_event_derived"},{"name":"gistic"},{"name":"gistic_to_gene"},{"name":"info"},{"name":"mut_sig"},{"name":"mutation"},{"name":"mutation_count_by_keyword"},{"name":"mutation_derived"},{"name":"mutation_event"},{"name":"mutation_panel_gene_coverage"},{"name":"mutation_wes_coverage"},{"name":"patient"},{"name":"reference_genome"},{"name":"reference_genome_gene"},{"name":"resource_definition"},{"name":"resource_patient"},{"name":"resource_sample"},{"name":"resource_study"},{"name":"sample"},{"name":"sample_cna_event"},{"name":"sample_derived"},{"name":"sample_list"},{"name":"sample_list_list"},{"name":"sample_profile"},{"name":"sample_to_gene_panel_derived"},{"name":"structural_variant"},{"name":"sv_panel_gene_coverage"},{"name":"sv_wes_coverage"},{"name":"top_cna_genes_in_study"},{"name":"top_mutated_genes_in_cohort"},{"name":"top_mutated_genes_in_study"},{"name":"top_sv_genes_in_study"},{"name":"treatment_counts_in_study"},{"name":"treatment_regimens_in_study"},{"name":"type_of_cancer"}]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT 
    cancer_study_identifier,
    hugo_gene_symbol,
    mutation_variant,
    mutation_type,
    COUNT(DISTINCT sample_unique_id) AS sample_count,
    COUNT(*) AS mutation_event_count
FROM genomic_event_derived
WHERE hugo_gene_symbol = 'CDKN2A'
  AND mutation_variant LIKE '%P135L%'
  AND variant_type = 'mutation'
  AND mutation_status != 'UNCALLED'
GROUP BY cancer_study_identifier, hugo_gene_symbol, mutation_variant, mutation_type
ORDER BY sample_count DESC
LIMIT 100
",
 "max_rows": 100
}

◀ result
{"rows":[]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT 
    mutation_variant,
    COUNT(DISTINCT sample_unique_id) AS sample_count,
    COUNT(DISTINCT cancer_study_identifier) AS study_count
FROM genomic_event_derived
WHERE hugo_gene_symbol = 'CDKN2A'
  AND variant_type = 'mutation'
  AND mutation_status != 'UNCALLED'
GROUP BY mutation_variant
ORDER BY sample_count DESC
LIMIT 30
",
 "max_rows": 100
}

◀ result
{"rows":[{"mutation_variant":"R80*","sample_count":1197,"study_count":148},{"mutation_variant":"R58*","sample_count":807,"study_count":108},{"mutation_variant":"H83Y","sample_count":734,"study_count":121},{"mutation_variant":"X51_splice","sample_count":516,"study_count":105},{"mutation_variant":"W110*","sample_count":387,"study_count":88},{"mutation_variant":"Y44*","sample_count":371,"study_count":65},{"mutation_variant":"X153_splice","sample_count":217,"study_count":65},{"mutation_variant":"P114L","sample_count":215,"study_count":55},{"mutation_variant":"L16Pfs*9","sample_count":208,"study_count":33},{"mutation_variant":"D84N","sample_count":203,"study_count":64},{"mutation_variant":"E120*","sample_count":188,"study_count":63},{"mutation_variant":"E88*","sample_count":151,"study_count":47},{"mutation_variant":"E69*","sample_count":143,"study_count":39},{"mutation_variant":"V28_E33del","sample_count":140,"study_count":32},{"mutation_variant":"D108N","sample_count":133,"study_count":47},{"mutation_variant":"P48L","sample_count":128,"study_count":47},{"mutation_variant":"D108Y","sample_count":123,"study_count":41},{"mutation_variant":"P81L","sample_count":122,"study_count":45},{"mutation_variant":"E61*","sample_count":120,"study_count":31},{"mutation_variant":"D84Y","sample_count":115,"study_count":44},{"mutation_variant":"S12*","sample_count":110,"study_count":42},{"mutation_variant":"L78Hfs*41","sample_count":107,"study_count":48},{"mutation_variant":"X50_splice","sample_count":103,"study_count":45},{"mutation_variant":"W15*","sample_count":96,"study_count":33},{"mutation_variant":"Q50*","sample_count":92,"study_count":37},{"mutation_variant":"H83D","sample_count":84,"study_count":34},{"mutation_variant":"A102V","sample_count":78,"study_count":40},{"mutation_variant":"Y129*","sample_count":78,"study_count":30},{"mutation_variant":"L32_L37del","sample_count":72,"study_count":25},{"mutation_variant":"D74N","sample_count":60,"study_count":30}]}

═ answer (success)
**P135L mutations in CDKN2A (p14^ARF^) were not found in cBioPortal.**

The database contains many CDKN2A mutations across 148 studies, but **P135L is not among them**. The closest similar variants are:
- **P114L** — 215 samples across 55 studies
- **P81L** — 122 samples across 45 studies  
- **P48L** — 128 samples across 47 studies

The top CDKN2A mutations overall are nonsense/frameshift alterations (R80*, R58*, truncations), followed by common missense variants like **H83Y** (734 samples).

**Possible explanations:**
1. **P135L is genuinely rare** — it may occur in <0.1% of profiled samples and isn't captured in this deployment
2. **Different isoform notation** — p14^ARF^ and p16^INK4A^ are products of the same *CDKN2A* gene; if you meant the p16 isoform, the same P135 position might map differently
3. **External cohort** — the mutation may be reported in literature or specialty databases not integrated into this cBioPortal instance

**To explore further:**
- Would you like me to search for P135L in a different gene, or look for other common CDKN2A variants?
- Do you have a specific cancer type or study in mind where you expect to find P135L?