Q (haiku): What are the top 5 most frequently copy number altered genes in the Osteosarcoma study from TARGET?

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

▶ list_studies
{
 "search": "TARGET osteosarcoma"
}

◀ 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 … (35166 more chars)

◀ result
{"result":[{"cancer_study_identifier":"os_target_gdc","name":"Osteosarcoma (TARGET GDC, 2025)","type_of_cancer_id":"os","sample_count":159,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=os_target_gdc"}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT hugo_gene_symbol, cna_type, altered_samples, profiled_samples, frequency_pct
FROM top_cna_genes_in_study(study = 'os_target_gdc', top_n = 5)"
}

◀ result
{"rows":[{"hugo_gene_symbol":"LINC00901","cna_type":"HOMDEL","altered_samples":32,"profiled_samples":81,"frequency_pct":39.5},{"hugo_gene_symbol":"RN7SL442P","cna_type":"AMP","altered_samples":31,"profiled_samples":81,"frequency_pct":38.3},{"hugo_gene_symbol":"ALKBH5","cna_type":"AMP","altered_samples":30,"profiled_samples":81,"frequency_pct":37},{"hugo_gene_symbol":"ATPAF2","cna_type":"AMP","altered_samples":30,"profiled_samples":81,"frequency_pct":37},{"hugo_gene_symbol":"BRI3P3","cna_type":"AMP","altered_samples":30,"profiled_samples":81,"frequency_pct":37}]}

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

◀ result
{"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"os_target_gdc","name":"Osteosarcoma (TARGET GDC, 2025)","sampleCount":159,"studyViewUrl":"https://www.cbioportal.org/study?id=os_target_gdc","metadata":{"clinicalAttributeIds":["AGE","CANCER_TYPE","CANCER_TYPE_DETAILED","DAYS_TO_BIRTH","DAYS_TO_DEATH","DISEASE_TYPE","ETHNICITY","MUTATION_COUNT","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","PRIMARY_DIAGNOSIS","PRIMARY_SITE_PATIENT","PROJECT_ID","RACE","SAMPLE_COUNT","SEX","SPECIMEN_TYPE","TMB_NONSYNONYMOUS","VITAL_STATUS"],"molecularProfileIds":["os_target_gdc_cna","os_target_gdc_mrna_seq_fpkm","os_target_gdc_mrna_seq_fpkm_Zscores","os_target_gdc_mrna_seq_read_counts_Zscores","os_target_gdc_mrna_seq_tpm","os_target_gdc_mrna_seq_tpm_Zscores","os_target_gdc_mutations","os_target_gdc_rna_seq_mrna"],"heatmapProfileIds":["os_target_gdc_mrna_seq_fpkm_Zscores","os_target_gdc_mrna_seq_read_counts_Zscores","os_target_gdc_mrna_seq_tpm_Zscores"],"availableComparisonTabs":["overlap","clinical","survival","alterations","mutations","mrna"]}}]}}

═ answer (success)
## Top 5 Most Frequently Copy Number Altered Genes in Osteosarcoma (TARGET GDC)

Based on analysis of the **Osteosarcoma (TARGET GDC, 2025)** cohort (159 samples, 81 with CNA profiling):

| Gene | CNA Type | Altered Samples | Frequency |
|------|----------|-----------------|-----------|
| LINC00901 | Homozygous Deletion | 32/81 | 39.5% |
| RN7SL442P | Amplification | 31/81 | 38.3% |
| ALKBH5 | Amplification | 30/81 | 37.0% |
| ATPAF2 | Amplification | 30/81 | 37.0% |
| BRI3P3 | Amplification | 30/81 | 37.0% |

**Key findings:** 
- LINC00901 shows the highest copy number alteration frequency at 39.5%, predominantly as a homozygous deletion
- The other top genes (RN7SL442P, ALKBH5, ATPAF2, BRI3P3) are amplified at similar frequencies (37–38%)
- Only 81 of 159 samples have CNA profiling data in this study

[View the Osteosarcoma study in cBioPortal](https://www.cbioportal.org/study?id=os_target_gdc)