{"id":"W2310742968","doi":"10.1534/g3.115.021667","title":"LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms","year":2015,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":481,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Canada Research Chairs; Genome Canada","keywords":"Imputation (statistics); Genotyping; Genotype; Missing data; Biology; Genomic selection; Genome-wide association study; Genome; Genomics; Computational biology; Genetics; Computer science; Single-nucleotide polymorphism; Gene; Machine learning","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":[0.00664334,0.001903084,0.002396148,0.002491825,0.001440131,0.00280334,0.005732679,0.002343858,0.01511102],"category_scores_gemma":[0.01915838,0.002122251,0.002539179,0.003168706,0.0006880442,0.002595197,0.003706596,0.00349466,0.01396057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007052873,"about_ca_system_score_gemma":0.001777422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003745589,"about_ca_topic_score_gemma":0.006416261,"domain_scores_codex":[0.9969399,0.001173102,0.0001740978,0.0006941013,0.0008577221,0.0001610753],"domain_scores_gemma":[0.9939924,0.003305621,0.0006804789,0.001269651,0.0005516365,0.0002002572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001561427,0.0004799101,0.02614103,0.002221258,0.003549259,0.001113135,0.001112897,0.1430892,0.02091539,0.0238015,0.2918262,0.4841889],"study_design_scores_gemma":[0.0005494399,0.0002291084,0.01022708,0.0003117921,0.000487511,0.0008937158,0.0001271397,0.7734869,0.0189259,0.05461169,0.1397813,0.0003684941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00528751,0.0004101161,0.9193304,0.0002322402,0.000144432,0.00008027792,0.01066642,0.06260967,0.001238885],"genre_scores_gemma":[0.05053641,0.0006266264,0.8704209,0.0004774197,0.0001358196,0.0009862157,0.05191469,0.02037072,0.004531217],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01511102,"threshold_uncertainty_score":0.05055141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02402387547798219,"score_gpt":0.2646507965306267,"score_spread":0.2406269210526445,"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."}}