{"id":"W3108703221","doi":"10.1101/2020.11.25.396721","title":"Current methods integrating variant functional annotation scores have limited capacity to improve the power of genome-wide association studies","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Toronto","keywords":"Genome-wide association study; Heritability; Biobank; Genetic association; Imputation (statistics); Statistical power; Annotation; Computational biology; Statistics; Computer science; Biology; Genetics; Single-nucleotide polymorphism; Mathematics; Missing data; 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":[0.1291557,0.003882981,0.004698782,0.009063971,0.001912903,0.007647206,0.005238994,0.002749205,0.006806578],"category_scores_gemma":[0.3222268,0.001984742,0.006563618,0.01412244,0.00419049,0.006667731,0.005520477,0.006051817,0.003246517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001120654,"about_ca_system_score_gemma":0.002297834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005502295,"about_ca_topic_score_gemma":0.006231076,"domain_scores_codex":[0.904681,0.06037942,0.006413307,0.01627337,0.01100843,0.001244538],"domain_scores_gemma":[0.6771861,0.2536458,0.01056688,0.04816698,0.009250573,0.001183604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001663408,0.0003430999,0.2612118,0.00401971,0.02075193,0.0003982364,0.000870507,0.04184601,0.008872801,0.0270961,0.01728493,0.6156415],"study_design_scores_gemma":[0.001136386,0.001341002,0.1554499,0.001953028,0.008141269,0.002134214,0.0007333884,0.4193579,0.0128478,0.3390429,0.05685883,0.001003414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03437959,0.006854765,0.9427263,0.001980147,0.0005681385,0.000375826,0.00447583,0.004849884,0.003789447],"genre_scores_gemma":[0.437822,0.002373006,0.548806,0.002354833,0.0008458269,0.000823861,0.003939871,0.001456063,0.001578607],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1291557,"threshold_uncertainty_score":0.6830487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03729883167756205,"score_gpt":0.2949883908655903,"score_spread":0.2576895591880282,"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."}}