{"id":"W2952683761","doi":"10.1186/s12859-018-2289-9","title":"PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores","year":2018,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital; Canadian Institute for Advanced Research; University of British Columbia; McGill University; Douglas Mental Health University Institute","funders":"Health Canada; Ludmer Centre for Neuroinformatics and Mental Health; Fondation Brain Canada; McGill University; Canadian Institute for Advanced Research","keywords":"Single-nucleotide polymorphism; SNP; Major depressive disorder; Software; Biology; Computer science; Computational biology; Statistics; Genetics; Mathematics; Gene; Genotype","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":[0.005310497,0.002429238,0.001682564,0.002071726,0.001300136,0.002233676,0.005269041,0.001073321,0.006682645],"category_scores_gemma":[0.01600729,0.001553661,0.00338506,0.002151088,0.001080306,0.002154224,0.004262171,0.002432502,0.004266073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009063196,"about_ca_system_score_gemma":0.003970991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007961027,"about_ca_topic_score_gemma":0.008724018,"domain_scores_codex":[0.9976588,0.0004783832,0.0002265239,0.0007885569,0.0006407765,0.0002068039],"domain_scores_gemma":[0.995411,0.002057821,0.0004094368,0.0009380418,0.0006962404,0.0004875333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003108851,0.0007732154,0.05426003,0.002040915,0.002878374,0.00234321,0.002195949,0.1735959,0.01472431,0.04297535,0.376263,0.324841],"study_design_scores_gemma":[0.001038944,0.0001746211,0.005727374,0.00007820228,0.0001917024,0.0006372913,0.0001898912,0.8556231,0.006575886,0.08142159,0.04812164,0.000219815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03291332,0.0005735948,0.7108135,0.001082779,0.0005567648,0.0006538681,0.01430688,0.2334234,0.005676082],"genre_scores_gemma":[0.2131492,0.0005940776,0.702602,0.001353972,0.0003383833,0.001629857,0.0440793,0.03231623,0.00393687],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007961027,"threshold_uncertainty_score":0.02808487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02616168096070415,"score_gpt":0.2715539279775312,"score_spread":0.245392247016827,"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."}}