{"id":"W2177764460","doi":"10.1093/bioinformatics/btv619","title":"ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations","year":2015,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Common Fund; National Eye Institute; National Human Genome Research Institute; African Institute for Mathematical Sciences; Division of Mathematical Sciences; Government of Canada; National Institutes of Health; University of Cape Town; International Development Research Centre","keywords":"Genome-wide association study; Linkage disequilibrium; Genetic association; Interactome; Biology; Computational biology; Breast cancer; Genetics; Single-nucleotide polymorphism; Gene; Cancer; Genotype","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000906536,0.000116813,0.0002481453,0.0001459434,0.0000771948,0.00003454437,0.00006038054,0.0001479255,0.000001565132],"category_scores_gemma":[0.001524608,0.0001129439,0.00005340446,0.0002103702,0.00001310269,0.00001296628,0.00006378896,0.0000643677,0.00000113826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006625041,"about_ca_system_score_gemma":0.00007569254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001093952,"about_ca_topic_score_gemma":0.001472678,"domain_scores_codex":[0.9990183,0.0001061669,0.0004337287,0.0001682558,0.00008342163,0.0001901592],"domain_scores_gemma":[0.999141,0.0001176426,0.0002804677,0.0001620814,0.0002087199,0.00009003491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003147125,0.00009111918,0.9941671,0.00001275594,0.0002407608,3.482628e-7,0.001089975,0.002096028,0.0001761337,0.00001097264,0.0003336472,0.001749611],"study_design_scores_gemma":[0.001255951,0.0006952231,0.9551859,0.000003819813,0.0002691336,0.00000483107,0.006806199,0.03181761,0.00006295898,0.000255141,0.003403306,0.0002398632],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.95056,0.0002132059,0.04826283,0.0002913396,0.0000851092,0.0003976521,0.00008361089,0.000007958749,0.00009828679],"genre_scores_gemma":[0.9395587,0.00004919272,0.05948836,0.0002885327,0.0000507323,0.00005690091,0.0003750578,0.000008073552,0.0001243889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03898122,"threshold_uncertainty_score":0.4605719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04406702794337682,"score_gpt":0.3328874962691267,"score_spread":0.2888204683257499,"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."}}