{"id":"W2007988561","doi":"10.1186/s13073-015-0138-2","title":"Rare variant association studies: considerations, challenges and opportunities","year":2015,"lang":"en","type":"article","venue":"Genome Medicine","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":254,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"Genome Canada; Canadian Institutes of Health Research; Fondation Institut de Cardiologie de Montréal; Institut de Cardiologie de Montréal; National Heart, Lung, and Blood Institute; Génome Québec","keywords":"Genetic architecture; Genetic association; Genome-wide association study; Heritability; Computational biology; Biology; Trait; Context (archaeology); Genotyping; Exome; Genetics; In silico; Human genetics; Missing heritability problem; Genetic variants; Phenotype; Exome sequencing; Evolutionary biology; Computer science; Single-nucleotide polymorphism; Genotype; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001307263,0.0001044922,0.0002333907,0.00004061406,0.00008322267,0.000004205633,0.00004125526,0.0001183469,0.00002005265],"category_scores_gemma":[0.003163445,0.00008581343,0.0000178991,0.00001614261,0.00008149898,0.000002563371,0.00006324642,0.0000522893,0.000004366323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000489767,"about_ca_system_score_gemma":0.00009105921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005537222,"about_ca_topic_score_gemma":0.00002208406,"domain_scores_codex":[0.9990903,0.0001669402,0.0002311455,0.0002071426,0.0001139428,0.0001904971],"domain_scores_gemma":[0.9991767,0.0001249653,0.0001350953,0.000158084,0.0002817224,0.0001234502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001603677,0.0002511632,0.01609425,0.0002844541,0.003205188,0.000171946,0.04103458,0.0004152894,0.03435962,0.04438925,0.828371,0.03126287],"study_design_scores_gemma":[0.004153265,0.00224652,0.06330752,0.00006181788,0.000253907,0.0002633189,0.03677884,0.00009183875,0.0002094597,0.04050462,0.8514662,0.0006627139],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4420225,0.3850583,0.0006763359,0.1489717,0.000954878,0.0004141974,0.00003212488,0.00004481681,0.0218252],"genre_scores_gemma":[0.9337106,0.05642817,0.0009030055,0.003468405,0.0008797104,0.00003578508,0.0001071879,0.00001425387,0.00445287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4916881,"threshold_uncertainty_score":0.3787168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1603933810641698,"score_gpt":0.3212143113594064,"score_spread":0.1608209302952366,"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."}}