{"id":"W3094583419","doi":"10.1371/journal.pcbi.1008336","title":"LocusFocus: Web-based colocalization for the annotation and functional follow-up of GWAS","year":2020,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; 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; Biology; Colocalization; Locus (genetics); Genetics; Quantitative trait locus; Computational biology; Genetic association; Linkage disequilibrium; Gene; Single-nucleotide polymorphism; Allele; Haplotype; Genotype; Molecular biology","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":[0.005287868,0.002080981,0.002380019,0.005153073,0.001295143,0.002265172,0.003308288,0.001647628,0.04944623],"category_scores_gemma":[0.01435899,0.001496408,0.003064149,0.003157285,0.000961992,0.002093775,0.005628349,0.001655228,0.01417533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006582208,"about_ca_system_score_gemma":0.001724988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003041202,"about_ca_topic_score_gemma":0.006837036,"domain_scores_codex":[0.998052,0.0005836814,0.0001415596,0.0006057934,0.0004326818,0.0001842549],"domain_scores_gemma":[0.9933294,0.004326988,0.0004563387,0.001160127,0.000336143,0.0003909862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005883451,0.0006988134,0.06862602,0.004419128,0.004569733,0.002961239,0.002527735,0.01674977,0.03406339,0.02438141,0.5251688,0.3099505],"study_design_scores_gemma":[0.003696827,0.000712238,0.07303118,0.000890446,0.001512812,0.003778879,0.001107938,0.3920804,0.06023091,0.13947,0.3224469,0.001041421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02566619,0.001332356,0.456457,0.0006453015,0.0003991536,0.000401399,0.07591933,0.4343053,0.004873929],"genre_scores_gemma":[0.2011751,0.0007901993,0.6154059,0.001181441,0.0002262501,0.002536119,0.09476192,0.07756682,0.0063564],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04944623,"threshold_uncertainty_score":0.1654141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02951483153121186,"score_gpt":0.258211786727303,"score_spread":0.2286969551960912,"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."}}