{"id":"W2996817667","doi":"10.1101/2020.01.02.891291","title":"LocusFocus: A web-based colocalization tool for the annotation and functional follow-up of GWAS","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Public Health Ontario; University of Toronto; Hospital for Sick Children","funders":"Hospital for Sick Children; Ontario Genomics Institute; Natural Sciences and Engineering Research Council of Canada; Cystic Fibrosis Canada; Canadian Institutes of Health Research; Genome Canada; Ontario Genomics; Cystic Fibrosis Foundation","keywords":"Genome-wide association study; Expression quantitative trait loci; Colocalization; Linkage disequilibrium; Biology; Computational biology; Quantitative trait locus; Genetic association; Genetics; Locus (genetics); Genome; False positive paradox; Gene; Allele; Single-nucleotide polymorphism; Computer science; Haplotype; Genotype; Artificial intelligence","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":[0.005214376,0.002357999,0.002515041,0.007080953,0.001376332,0.002342441,0.003659391,0.001766889,0.06824186],"category_scores_gemma":[0.01139993,0.001751687,0.002307346,0.003682562,0.0008735475,0.002238068,0.005628789,0.001833412,0.02518643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006661054,"about_ca_system_score_gemma":0.001522135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002290093,"about_ca_topic_score_gemma":0.003352832,"domain_scores_codex":[0.9978225,0.0004403287,0.0001746073,0.0005798045,0.0007779661,0.0002048648],"domain_scores_gemma":[0.9939005,0.003571729,0.0004318702,0.001291447,0.0003820528,0.0004223589],"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":[0.002580727,0.0004139904,0.02414573,0.002915108,0.00163762,0.002390709,0.001156514,0.005534449,0.03494913,0.01554486,0.7230868,0.1856444],"study_design_scores_gemma":[0.003518281,0.0004966992,0.05800435,0.001093837,0.001099207,0.006462639,0.0008278152,0.1694144,0.0939766,0.109459,0.5545356,0.00111167],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.01174784,0.0007941033,0.3493807,0.0004277538,0.0002334943,0.0003236217,0.1003423,0.5323247,0.004425452],"genre_scores_gemma":[0.1259674,0.000710282,0.5469784,0.0008386996,0.000245295,0.002536118,0.1853958,0.129855,0.007472971],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.06824186,"threshold_uncertainty_score":0.2282917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01665646827588161,"score_gpt":0.2303771452869683,"score_spread":0.2137206770110867,"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."}}