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

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

▶ resolve_and_route
{
 "studyKeywords": [
  "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
{"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"]}}]}}

▶ 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 *
FROM top_sv_genes_in_study(study = 'os_target_gdc', top_n = 5)
ORDER BY altered_samples DESC
"
}

◀ result
{"rows":[]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT DISTINCT variant_type
FROM genomic_event_derived
WHERE cancer_study_identifier = 'os_target_gdc'
ORDER BY variant_type
"
}

◀ result
{"rows":[{"variant_type":"cna"},{"variant_type":"mutation"}]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT 
    genetic_profile_id,
    name,
    genetic_alteration_type,
    datatype
FROM genetic_profile
WHERE cancer_study_identifier = 'os_target_gdc'
ORDER BY genetic_profile_id
"
}

◀ result
{"error_message":"Query execution failed: HTTPDriver for https://dl96orhu96.us-east-1.aws.clickhouse.cloud:8443 received ClickHouse error code 47\n Code: 47. DB::Exception: Unknown expression or function identifier `cancer_study_identifier` in scope SELECT genetic_profile_id, name, genetic_alteration_type, datatype FROM genetic_profile WHERE cancer_study_identifier = 'os_target_gdc' ORDER BY genetic_profile_id ASC. (UNKNOWN_IDENTIFIER) (version 26.4.1.2359 (official build))\n"}

▶ clickhouse_list_table_columns
{
 "table": "genetic_profile"
}

◀ result
{"columns":[{"name":"genetic_profile_id","type":"Int64"},{"name":"stable_id","type":"String"},{"name":"cancer_study_id","type":"Int64"},{"name":"genetic_alteration_type","type":"String"},{"name":"generic_assay_type","type":"Nullable(String)"},{"name":"datatype","type":"String"},{"name":"name","type":"String"},{"name":"description","type":"Nullable(String)"},{"name":"show_profile_in_analysis_tab","type":"Int32"},{"name":"pivot_threshold","type":"Nullable(Float64)"},{"name":"sort_order","type":"Nullable(String)"},{"name":"patient_level","type":"Nullable(Int32)"}]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT 
    gp.stable_id,
    gp.name,
    gp.genetic_alteration_type,
    gp.datatype
FROM genetic_profile gp
JOIN cancer_study cs ON gp.cancer_study_id = cs.cancer_study_id
WHERE cs.cancer_study_identifier = 'os_target_gdc'
ORDER BY gp.stable_id
"
}

◀ result
{"rows":[{"stable_id":"os_target_gdc_cna","name":"Putative copy-number alterations from GISTIC","genetic_alteration_type":"COPY_NUMBER_ALTERATION","datatype":"DISCRETE"},{"stable_id":"os_target_gdc_mrna_seq_fpkm","name":"mRNA Expression (FPKM)","genetic_alteration_type":"MRNA_EXPRESSION","datatype":"CONTINUOUS"},{"stable_id":"os_target_gdc_mrna_seq_fpkm_Zscores","name":"mRNA Expression FPKM z-scores","genetic_alteration_type":"MRNA_EXPRESSION","datatype":"Z-SCORE"},{"stable_id":"os_target_gdc_mrna_seq_read_counts_Zscores","name":"mRNA Expression z-scores","genetic_alteration_type":"MRNA_EXPRESSION","datatype":"Z-SCORE"},{"stable_id":"os_target_gdc_mrna_seq_tpm","name":"mRNA Expression (TPM)","genetic_alteration_type":"MRNA_EXPRESSION","datatype":"CONTINUOUS"},{"stable_id":"os_target_gdc_mrna_seq_tpm_Zscores","name":"mRNA Expression TPM z-scores","genetic_alteration_type":"MRNA_EXPRESSION","datatype":"Z-SCORE"},{"stable_id":"os_target_gdc_mutations","name":"Mutations","genetic_alteration_type":"MUTATION_EXTENDED","datatype":"MAF"},{"stable_id":"os_target_gdc_rna_seq_mrna","name":"mRNA Expression","genetic_alteration_type":"MRNA_EXPRESSION","datatype":"CONTINUOUS"}]}

═ answer (success)
Perfect! As confirmed, the TARGET Osteosarcoma study (os_target_gdc) has **no structural variant (SV) data**. The available data types are:
- Copy-number alterations (CNA)
- Mutations
- mRNA Expression

## Answer

The **TARGET Osteosarcoma study (os_target_gdc) does not contain structural variant data**. 

The study's molecular profiling includes:
- **Mutations** (MAF format)
- **Copy-number alterations** (discrete GISTIC calls)
- **mRNA expression** (multiple formats: FPKM, TPM, z-scores)

There is no structural variant profiling available in this cohort. If you're interested in the most frequently altered genes by **mutations** or **copy-number alterations** in this osteosarcoma cohort instead, I'd be happy to provide that analysis. Would you like me to query for the top mutated or CNA genes?