{"id":"W2132145985","doi":"10.1002/gepi.20164","title":"Stratified false discovery control for large‐scale hypothesis testing with application to genome‐wide association studies","year":2006,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":158,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; U.S. Public Health Service; Canada Research Chairs","keywords":"False discovery rate; Multiple comparisons problem; False positive paradox; Population stratification; Computational biology; Statistics; Genome-wide association study; Statistical power; Hum; Statistical hypothesis testing; Genetic association; False positives and false negatives; Computer science; Biology; Mathematics; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1335277,0.002971719,0.003958386,0.004328357,0.001843669,0.003290245,0.00723921,0.004710075,0.005960165],"category_scores_gemma":[0.342924,0.001328651,0.004453022,0.006158032,0.006761222,0.003525849,0.005525986,0.008210668,0.001255532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002772365,"about_ca_system_score_gemma":0.005940855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003004914,"about_ca_topic_score_gemma":0.00256458,"domain_scores_codex":[0.8737256,0.1019344,0.003582054,0.007766704,0.01170557,0.00128572],"domain_scores_gemma":[0.6724391,0.2825164,0.01263174,0.02178778,0.009235637,0.001389315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001804009,0.0004456301,0.01359192,0.002272484,0.003275758,0.002498642,0.001880565,0.1353774,0.008419987,0.4619533,0.01607858,0.3524016],"study_design_scores_gemma":[0.0005471453,0.0007842677,0.004436781,0.000375062,0.0006654625,0.0008563675,0.0001212749,0.6261613,0.006722088,0.3407371,0.01836667,0.0002263965],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001401578,0.000498009,0.9967394,0.0001723335,0.0001575556,0.0002500131,0.00006228626,0.0003485138,0.000370219],"genre_scores_gemma":[0.07660995,0.0005521171,0.9185151,0.0005477492,0.0003215427,0.002270322,0.0002508568,0.0002949876,0.0006374824],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1335277,"threshold_uncertainty_score":0.7061706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02547525894508838,"score_gpt":0.2835608180684288,"score_spread":0.2580855591233404,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}