{"id":"gdc-tcga-brca","title":"Breast Invasive Carcinoma","short_title":"TCGA-BRCA","aliases":["tcga_brca"],"summary":"TCGA breast is the most heavily analyzed dataset indexed here: 2,463 articles reference it in their methods or results. Its continuing value is less about novelty than about being the common denominator - a cohort so widely used that a new method which cannot reproduce known findings on it is not yet credible.\nTwo things about it are less widely appreciated. First, its radiology and pathology imaging lives in the Imaging Data Commons rather than the GDC, so the same 1,098 patients carry twelve measurement types once the repositories are joined, and most analyses use only the genomic subset. 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Please see the DICOM converted Slide Microscopy images for the TCGA-BRCA collection page to learn more about the histopathology images and to obtain any supporting metadata for th","locator":"accession extracted from description prose","confidence":"medium","reviewer":null,"reviewed_at":null,"note":"Cross-repository link recovered from prose; verify before relying on it."}]}],"repository":{"name":"NCI Genomic Data Commons","short_name":"GDC","url":"https://portal.gdc.cancer.gov","is_nci_crdc_node":true,"is_nih_repository":true},"additional_repositories":[{"name":"NCI Imaging Data 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Resolved from RePORTER's publication index; only a repository-supplied or reviewer-supplied marker paper is used, never one this pipeline nominated itself."}]},{"core_project_num":"R01CA094143","project_num":null,"title":"ADA3: a novel target for HPV16 E6 oncoprotein","pi_names":["VIMLA BAND"],"agency_ic":"NCI","activity_code":"R01","fiscal_years":[2002,2003,2004,2005,2006],"award_amount_usd":1704746,"org_name":"ENDEAVOR HEALTH CLINICAL OPERATIONS","reporter_url":"https://reporter.nih.gov/search/results?text_criteria=R01CA094143","role":"generation","evidence":[{"method":"api","source_url":"https://api.reporter.nih.gov/v2/publications/search","source_label":"NIH RePORTER","retrieved_at":"2026-09-20T17:21:14.041075Z","snippet":null,"locator":"PMID 23000897 (this dataset's marker paper) reported under R01CA094143","confidence":"high","reviewer":null,"reviewed_at":null,"note":"The award is credited on the dataset's own marker paper, so it paid to produce these data rather than to analyse them. 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Hawse","Vera Jean Suman","MARK E SHERMAN","Amy C Degnim","Daniel Visscher","Evanthia Galanis","JAMES Newell INGLE","Liewei Wang","PAUL HALUSKA","Wilma Lingle","CELINE M VACHON","SANDRA J GENDLER","Junjie Chen"],"agency_ic":"NCI","activity_code":"P50","fiscal_years":[2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023,2024,2025,2026],"award_amount_usd":89458712,"org_name":"MAYO CLINIC ROCHESTER","reporter_url":"https://reporter.nih.gov/search/results?text_criteria=P50CA116201","role":"generation","evidence":[{"method":"api","source_url":"https://api.reporter.nih.gov/v2/publications/search","source_label":"NIH RePORTER","retrieved_at":"2026-09-20T17:21:14.041075Z","snippet":null,"locator":"PMID 23000897 (this dataset's marker paper) reported under P50CA116201","confidence":"high","reviewer":null,"reviewed_at":null,"note":"The award is credited on the dataset's own marker paper, so it paid to produce these data rather than to analyse them. Resolved from RePORTER's publication index; only a repository-supplied or reviewer-supplied marker paper is used, never one this pipeline nominated itself."}]},{"core_project_num":"P50CA058223","project_num":null,"title":"SPORE in Breast Cancer","pi_names":["LISA A CAREY","Gaorav P. Gupta","CHARLES M PEROU","H. Shelton Earp","Melissa A. Troester","KATHERINE A. HOADLEY","BENJAMIN CARLISLE CALHOUN","Gianpietro Dotti","GARY L. JOHNSON","James Stephen Marron","Hector Luis Franco","James Todd Auman","ROBERT C MILLIKAN","shelton Earp","LEIGH B THORNE","Shelton Earp","Jonathan S. Serody","Nancy Demore","LYNN Gail DRESSLER","BAHJAT F QAQISH","KATHLEEN CONWAY DORSEY","EDISON T LIU","BETH NEWMAN","BOB MILLIKAN","WILLIAM G CANCE","JO ANNE L EARP","Barbara S Hulka"],"agency_ic":"NCI","activity_code":"P50","fiscal_years":[1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2012,2013,2014,2015,2016,2018,2019,2020,2021,2022,2024,2025,2026],"award_amount_usd":111432056,"org_name":"UNIV OF NORTH CAROLINA CHAPEL HILL","reporter_url":"https://reporter.nih.gov/search/results?text_criteria=P50CA058223","role":"generation","evidence":[{"method":"api","source_url":"https://api.reporter.nih.gov/v2/publications/search","source_label":"NIH RePORTER","retrieved_at":"2026-09-20T17:21:14.041075Z","snippet":null,"locator":"PMID 23000897 (this dataset's marker paper) reported under P50CA058223","confidence":"high","reviewer":null,"reviewed_at":null,"note":"The award is credited on the dataset's own marker paper, so it paid to produce these data rather than to analyse them. Resolved from RePORTER's publication index; only a repository-supplied or reviewer-supplied marker paper is used, never one this pipeline nominated itself."}]}],"access_steps":[{"order":1,"action":"Download open derived matrices from the GDC","detail":"Expression, copy number, methylation and clinical files need no account.","url":"https://portal.gdc.cancer.gov/projects/TCGA-BRCA","requires":[],"est_time":"1 hour","cli_snippet":"curl -s 'https://api.gdc.cancer.gov/files' --get \\\n  --data-urlencode 'filters={\"op\":\"and\",\"content\":[\n    {\"op\":\"in\",\"content\":{\"field\":\"cases.project.project_id\",\"value\":[\"TCGA-BRCA\"]}},\n    {\"op\":\"in\",\"content\":{\"field\":\"access\",\"value\":[\"open\"]}},\n    {\"op\":\"in\",\"content\":{\"field\":\"data_type\",\"value\":[\"Gene Expression Quantification\"]}}]}' \\\n  --data-urlencode 'fields=file_id,file_name,cases.submitter_id' \\\n  --data-urlencode 'size=2000&format=TSV' > brca_expression_files.tsv\n","audience":"human","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.908521Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"order":2,"action":"Add the imaging from the Imaging Data Commons if you need it","detail":"Same patients, different repository, also open. Most users never make this join.","url":"https://portal.imaging.datacommons.cancer.gov/explore/?collection_id=tcga_brca","requires":[],"est_time":"1-2 hours","cli_snippet":null,"audience":"human","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.908521Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"order":3,"action":"Request controlled access only if you need sequence-level data","detail":null,"url":"https://gdc.cancer.gov/access-data/obtaining-access-controlled-data","requires":["eRA Commons account","institutional signing official approval"],"est_time":"days to a few weeks","cli_snippet":null,"audience":"human","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.908521Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"order":4,"action":"Query the project from code, with no credentials","detail":"The file index is public even where files are not, so an agent can size the cohort before anyone requests access.","url":"https://docs.gdc.cancer.gov/API/Users_Guide/Getting_Started/","requires":[],"est_time":null,"cli_snippet":"curl -s 'https://api.gdc.cancer.gov/files' --get \\\n  --data-urlencode 'filters={\"op\":\"in\",\"content\":{\"field\":\"cases.project.project_id\",\"value\":[\"TCGA-BRCA\"]}}' \\\n  --data-urlencode 'fields=file_id,file_name,data_type' \\\n  --data-urlencode 'size=10000' --data-urlencode 'format=TSV'","audience":"agent","evidence":[{"method":"derived","source_url":"https://docs.gdc.cancer.gov/API/Users_Guide/Getting_Started/","source_label":"GDC access documentation","retrieved_at":"2026-09-21T12:30:59.428853Z","snippet":null,"locator":null,"confidence":"medium","reviewer":null,"reviewed_at":null,"note":"Generated by applying the repository's documented access policy to this dataset's identifiers. It is not a reviewer's account of this dataset."}]},{"order":5,"action":"Pass the token when the agent needs controlled files","detail":"Without a token, an API query may return only the open subset. Compare returned counts with the record before treating them as the whole cohort.","url":"https://docs.gdc.cancer.gov/API/Users_Guide/Getting_Started/","requires":["GDC authentication token"],"est_time":null,"cli_snippet":"curl -H \"X-Auth-Token: $GDC_TOKEN\" https://api.gdc.cancer.gov/data/<file_id>","audience":"agent","evidence":[{"method":"derived","source_url":"https://docs.gdc.cancer.gov/API/Users_Guide/Getting_Started/","source_label":"GDC access documentation","retrieved_at":"2026-09-21T12:30:59.428855Z","snippet":null,"locator":null,"confidence":"medium","reviewer":null,"reviewed_at":null,"note":"Generated by applying the repository's documented access policy to this dataset's identifiers. It is not a reviewer's account of this dataset."}]}],"analysis_examples":[{"level":"beginner","title":"Audit whether this dataset can answer your question","question":"Which classes of analysis do this cohort's clinical records actually support, and which are ruled out before I request access?","problem":"A portal can list a field even when every value is an unusable non-answer.","lesson":"Decide whether the analysis is possible before requesting data or writing a protocol.","figure":"Horizontal bars for each probed clinical field, showing the share of cases the field is populated for against the smaller share that carries an informative value, with one-to-many fields marked as not derivable per case.","featured":true,"inputs":["A GDC project identifier","Network access to api.gdc.cancer.gov"],"outputs":["Per-field coverage table separating populated from informative values","Assay coverage as a percentage of the cohort","A yes/no verdict for six common analysis classes","A chart contrasting populated with informative coverage, field by field"],"steps":["Fetch project summary and per-assay case counts","Request facet counts for the clinical fields that gate common analyses","Separate absent fields from fields populated with non-answers","Flag one-to-many fields where per-case percentages cannot be inferred","Retrieve case-level fields and test whether a survival endpoint is derivable","Print a verdict for each analysis class"],"findings":["Four of the six analysis classes pass for CGCI-HTMCP-CC; stage-adjusted modelling and progression-free endpoints are blocked.","Vital status is informative for all 212 cases with 116 deaths, so an overall-survival endpoint is derivable.","Both stage fields and the progression field are informative for 0% of cases, which no case count can fix.","Four fields hold several records per case, so their per-case share cannot be inferred from a facet count at all."],"contributor":null,"contributor_url":null,"language":"python","est_runtime":"about a minute","est_compute":null,"workbook_path":"workbooks/python/01_can_i_answer_this.py","workbook_url":null,"notebook_download_url":"/data/notebooks/01_can_i_answer_this.ipynb","notebook_preview_url":"/data/notebooks/01_can_i_answer_this.png","notebook_preview_width":1021,"notebook_preview_height":813,"colab_url":null,"binder_url":null,"receipt":{"executed":true,"executed_at":"2026-09-21T00:40:59.561676Z","runtime_seconds":6.57,"executor":"nbclient / python 3.12.13 / Darwin 25.5.0 arm64","package_versions":{"python":"3.12.13","pandas":"3.0.6","numpy":"2.5.3","matplotlib":"3.11.2","lifelines":"0.30.0","scipy":"1.18.1","requests":"2.34.2","httpx":"0.28.1"},"n_cells":7,"n_cells_executed":7,"output_hash":"dc14b4c93e7e9d6aff322ff2d0de47b8","data_retrieved_at":null,"error":null},"template_source":"01_can_i_answer_this","evidence":[{"method":"curated","source_url":null,"source_label":"CD2S workbook","retrieved_at":"2026-09-21T12:30:59.450276Z","snippet":null,"locator":"workbooks/python/01_can_i_answer_this.py","confidence":"high","reviewer":null,"reviewed_at":null,"note":"Executed end to end against the live public APIs; the receipt records when, with which package versions and how long it took."}]},{"level":"beginner","title":"Overall survival from open data, with the endpoint derived correctly","question":"Which molecular and clinical factors are associated with survival?","problem":"Survival time is split across three fields and includes sentinel values that look numeric.","lesson":"Derive a defensible endpoint, account for exclusions, then fit and interpret the model.","figure":"Kaplan-Meier survival curves against months since diagnosis: one curve for the whole cohort and one per stage group, showing separation between stages and how thin the long follow-up becomes.","featured":true,"inputs":["Open GDC clinical records, no account required","lifelines, pandas, numpy"],"outputs":["Kaplan-Meier estimates with survival at 12, 36 and 60 months","Log-rank test between stage groups","Multivariable Cox model with concordance","A Kaplan-Meier plot of overall survival, stratified by stage at diagnosis"],"steps":["Retrieve case-level clinical fields including all three follow-up locations","Derive time and event, guarding against GDC sentinel values","Report how many cases are dropped and why","Fit Kaplan-Meier and a stage-stratified log-rank test","Fit a multivariable Cox model adjusting for age and stage"],"findings":["1,076 of 1,098 cases carry a usable endpoint - 150 deaths, 926 censored, median follow-up 25.6 months among the censored.","Survival is 97.9% at 12 months, 89.8% at 36 and 81.9% at 60.","Stage I against stage IV separates sharply - log-rank p = 8.1e-18 on 183 against 20 cases.","The Cox model fits 1,050 cases with 141 events and reaches concordance 0.746; stage IV carries a hazard ratio of 10.6."],"contributor":null,"contributor_url":null,"language":"python","est_runtime":"about two minutes","est_compute":null,"workbook_path":"workbooks/python/02_survival_tcga_brca.py","workbook_url":null,"notebook_download_url":"/data/notebooks/02_survival_tcga_brca.ipynb","notebook_preview_url":"/data/notebooks/02_survival_tcga_brca.png","notebook_preview_width":1021,"notebook_preview_height":565,"colab_url":null,"binder_url":null,"receipt":{"executed":true,"executed_at":"2026-09-21T00:41:05.599807Z","runtime_seconds":5.0,"executor":"nbclient / python 3.12.13 / Darwin 25.5.0 arm64","package_versions":{"python":"3.12.13","pandas":"3.0.6","numpy":"2.5.3","matplotlib":"3.11.2","lifelines":"0.30.0","scipy":"1.18.1","requests":"2.34.2","httpx":"0.28.1"},"n_cells":8,"n_cells_executed":8,"output_hash":"ebd8b6e4107665e58a738df4af8fdbcd","data_retrieved_at":null,"error":null},"template_source":"02_survival_tcga_brca","evidence":[{"method":"curated","source_url":null,"source_label":"CD2S workbook","retrieved_at":"2026-09-21T12:30:59.450296Z","snippet":null,"locator":"workbooks/python/02_survival_tcga_brca.py","confidence":"high","reviewer":null,"reviewed_at":null,"note":"Executed end to end against the live public APIs; the receipt records when, with which package versions and how long it took."}]},{"level":"advanced","title":"Join the same patients across two NCI repositories","question":"Which cohorts have both imaging and molecular data on the same patients, and how many patients actually carry both?","problem":"Molecular and imaging data for the same cohort live in separate NCI repositories.","lesson":"Join shared patient identifiers and quantify the real multimodal overlap, not the advertised totals.","figure":"Paired horizontal bars per cohort comparing GDC molecular case counts with IDC imaging patient counts, where the shorter bar is the ceiling on a multimodal study of that cohort.","featured":true,"inputs":["Open GDC and IDC APIs, no account required","pandas"],"outputs":["Patient-level intersection between a GDC project and an IDC collection","Counts of molecular-only, imaging-only and joined patients","A map of every cohort present in both repositories","A chart comparing molecular and imaging patient counts per linkable cohort"],"steps":["Retrieve patient identifiers from the GDC project","Query IDC's public SQL endpoint for the collection's patient identifiers","Intersect on the shared barcode and quantify the overlap","Sweep every GDC project against every IDC collection"],"findings":["All 1,098 TCGA-BRCA patients appear in both the GDC and the IDC, a 100% join with nothing imaging-only.","39 cohorts exist in both repositories, covering 15,761 patients.","HCMI-CMDC holds 805 molecular cases but 382 imaging patients, so its multimodal ceiling is 382, not 805."],"contributor":null,"contributor_url":null,"language":"python","est_runtime":"about two minutes","est_compute":null,"workbook_path":"workbooks/python/05_cross_repository_linkage.py","workbook_url":null,"notebook_download_url":"/data/notebooks/05_cross_repository_linkage.ipynb","notebook_preview_url":"/data/notebooks/05_cross_repository_linkage.png","notebook_preview_width":1045,"notebook_preview_height":1045,"colab_url":null,"binder_url":null,"receipt":{"executed":true,"executed_at":"2026-09-21T00:43:01.297366Z","runtime_seconds":4.98,"executor":"nbclient / python 3.12.13 / Darwin 25.5.0 arm64","package_versions":{"python":"3.12.13","pandas":"3.0.6","numpy":"2.5.3","matplotlib":"3.11.2","lifelines":"0.30.0","scipy":"1.18.1","requests":"2.34.2","httpx":"0.28.1"},"n_cells":6,"n_cells_executed":6,"output_hash":"fe7a493665d23ae04c207c4b406923c9","data_retrieved_at":null,"error":null},"template_source":"05_cross_repository_linkage","evidence":[{"method":"curated","source_url":null,"source_label":"CD2S workbook","retrieved_at":"2026-09-21T12:30:59.450347Z","snippet":null,"locator":"workbooks/python/05_cross_repository_linkage.py","confidence":"high","reviewer":null,"reviewed_at":null,"note":"Executed end to end against the live public APIs; the receipt records when, with which package versions and how long it took."}]}],"agent_package":{"json_url":"/data/datasets/gdc-tcga-brca.json","jsonld_url":"/data/jsonld/gdc-tcga-brca.jsonld","croissant_url":"/data/croissant/gdc-tcga-brca.json","instructions_url":"/data/agent/gdc-tcga-brca.md","bundle_url":null,"mcp_resource_uri":null},"related_dataset_ids":[],"related_underexplored_ids":[],"review":{"status":"project_curated","reviewer":"CD2S project curation","reviewer_affiliation":null,"reviewed_at":"2026-09-18","sections_reviewed":["useful_for","limitations","inappropriate_uses","access_steps","primary_publications"],"open_questions":[],"notes":null},"verification":{"last_verified_at":null,"link_checks":[],"n_links_ok":0,"n_links_broken":0,"upstream_version_seen":null,"upstream_version_changed":false,"upstream_counts_seen":{},"upstream_drift":{},"notes":[]},"is_showcase":true,"completeness_score":100.0,"tags":["breast","gdc","has-derived-annotations","idc","imaging","imaging-genomics","imaging-pathology","multimodal","reference-cohort","released","tcga","treatment-response"],"search_text":null}