{"id":"W3207046163","doi":"10.1016/j.xhgg.2021.100063","title":"From GWAS variant to function: A study of ∼148,000 variants for blood cell traits","year":2021,"lang":"en","type":"article","venue":"Human Genetics and Genomics Advances","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"National Center for Advancing Translational Sciences; National Institute of General Medical Sciences; National Institute on Drug Abuse; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institutes of Health; New York Stem Cell Foundation","keywords":"Genome-wide association study; Computational biology; Phenome; Biology; Epigenomics; Genetic association; Gene; Genome; Quantitative trait locus; Function (biology); Chromatin; Genetics; Single-nucleotide polymorphism; DNA methylation; Gene expression; Genotype","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00209655,0.0005727035,0.0006830999,0.001919415,0.0007191261,0.001126789,0.0005267755,0.0007122621,0.002543406],"category_scores_gemma":[0.006250659,0.000311455,0.000913539,0.002236598,0.0004162625,0.0003262544,0.0009065343,0.0007559533,0.0007112334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002121937,"about_ca_system_score_gemma":0.0004028524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001391028,"about_ca_topic_score_gemma":0.002130344,"domain_scores_codex":[0.9985628,0.0003536904,0.0001108365,0.0006545639,0.0002265956,0.00009152905],"domain_scores_gemma":[0.9965959,0.001940259,0.0003908925,0.0006106315,0.0001952984,0.0002669639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001843429,0.0002212278,0.7872236,0.0005164222,0.002036434,0.003253276,0.0008494533,0.00172409,0.07457402,0.002492991,0.008029223,0.1172358],"study_design_scores_gemma":[0.000271768,0.0006158159,0.9389553,0.0001235474,0.001735879,0.007787509,0.0003227835,0.006678838,0.01262407,0.004865884,0.0259177,0.0001009156],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9780133,0.003450222,0.01111836,0.0003028843,0.00005057107,0.00004201779,0.005653748,0.0003521534,0.001016687],"genre_scores_gemma":[0.97602,0.0009082729,0.01344831,0.0003825347,0.000055172,0.00006691519,0.008142591,0.0002036219,0.0007727118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002543406,"threshold_uncertainty_score":0.01108772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01533002882195489,"score_gpt":0.2673678544881649,"score_spread":0.25203782566621,"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."}}