{"id":"W3134758003","doi":"10.1101/2021.03.05.433935","title":"Within-sibship GWAS improve estimates of direct genetic effects","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"Medical Research Council; National Institutes of Health; Jacobs Foundation; Research Councils UK; ZonMw; University of Bristol; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; British Heart Foundation","keywords":"Genome-wide association study; Assortative mating; Heritability; Biology; Genetic association; Population stratification; Mendelian randomization; Population; Additive genetic effects; Genetic architecture; Genetics; Genetic variation; Demography; Single-nucleotide polymorphism; Phenotype; Genetic variants; Genotype; Mating","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":[0.01143357,0.000810653,0.001748952,0.001653233,0.0006355537,0.001546914,0.0006131013,0.0005209183,0.005220869],"category_scores_gemma":[0.0251964,0.0005003113,0.0009153778,0.00242032,0.0005206105,0.0008611427,0.001914674,0.00113659,0.001078223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002208389,"about_ca_system_score_gemma":0.0004998749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002337574,"about_ca_topic_score_gemma":0.004081288,"domain_scores_codex":[0.992833,0.004671371,0.0003736538,0.001268844,0.000699777,0.0001532763],"domain_scores_gemma":[0.9778534,0.01333001,0.001825194,0.005669015,0.0009578271,0.0003645253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001012659,0.0002873736,0.8319322,0.0005012816,0.006128277,0.0005859089,0.0006669482,0.01541233,0.02584975,0.00519376,0.004594273,0.1078353],"study_design_scores_gemma":[0.0002319926,0.0002748682,0.9071804,0.0001599965,0.001975851,0.0009251649,0.0002938473,0.04696782,0.01143459,0.02130915,0.009172651,0.00007372425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8637595,0.001839894,0.123213,0.0004226605,0.0001870762,0.00005049568,0.00459939,0.001285675,0.00464229],"genre_scores_gemma":[0.9595966,0.0003388662,0.03587133,0.0002277815,0.00007473087,0.00004440369,0.002725011,0.0003365873,0.0007847107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01143357,"threshold_uncertainty_score":0.06046724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008315361350453306,"score_gpt":0.2247813803612735,"score_spread":0.2164660190108202,"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."}}