{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006217827,0.0005448925,0.0008502145,0.0001111951,0.00009941664,0.00006435128,0.000504957,0.0009893789,0.00001332995],"category_scores_gemma":[0.001574259,0.0005800796,0.0003013284,0.0002068028,0.0001659642,0.000004250817,0.0007207401,0.0004025988,0.000009551221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007010248,"about_ca_system_score_gemma":0.0007002672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008225182,"about_ca_topic_score_gemma":0.000009548092,"domain_scores_codex":[0.9970829,0.0002998519,0.0007335673,0.001118897,0.0002211743,0.0005436303],"domain_scores_gemma":[0.9969141,0.0001156378,0.0007591738,0.001445369,0.0005604149,0.0002052347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001772788,0.0001152262,0.0673392,0.0004853723,0.0004057943,0.00001682886,0.000007701557,0.0005237377,0.9307601,0.00002023244,0.0003031413,0.00000486741],"study_design_scores_gemma":[0.0003344693,0.0001648897,0.3005331,0.0001665674,0.0001954068,3.139153e-8,0.000003035577,0.000308587,0.6974472,0.000004245418,0.0003278912,0.0005144873],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868169,0.008149177,0.00284046,0.00006215079,0.001396207,0.0005278893,0.0001212366,0.00005935521,0.00002662939],"genre_scores_gemma":[0.968574,0.0009662392,0.02955234,0.0001670644,0.000431296,0.0001840997,0.000004130835,0.000110251,0.00001051454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2333129,"threshold_uncertainty_score":0.9996651,"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."}}