{"id":"W2952718909","doi":"10.1002/gepi.22131","title":"Transcriptome‐wide association studies accounting for colocalization using Egger regression","year":2018,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Human Genome Research Institute; National Institute of Mental Health; Health Canada; Translation Centre for the Bodies of the European Union; National Cancer Institute; National Institutes of Health; FAS Division of Science, Harvard University; Foundation for the National Institutes of Health; Cancer Research UK; Government of Canada; Harvard University; Genome Canada","keywords":"Colocalization; Association (psychology); Regression; Biology; Statistics; Mathematics; Molecular biology; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01524231,0.0009635197,0.001815619,0.001143133,0.0007055353,0.001292289,0.003227139,0.001779115,0.006557856],"category_scores_gemma":[0.04496454,0.0007536738,0.002921344,0.002211029,0.001176986,0.002121339,0.001507029,0.002161837,0.001015921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007844738,"about_ca_system_score_gemma":0.001230174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009310984,"about_ca_topic_score_gemma":0.008505,"domain_scores_codex":[0.9944886,0.003591166,0.0002205704,0.001088448,0.0004192716,0.0001918163],"domain_scores_gemma":[0.9774444,0.01741255,0.001419266,0.002847605,0.0007112668,0.000165008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005003919,0.00009975188,0.05318407,0.0006574029,0.002745331,0.001908246,0.0005109067,0.5458515,0.01453576,0.2574593,0.006726719,0.1158206],"study_design_scores_gemma":[0.0001253129,0.00009109035,0.007989259,0.00006242502,0.0003999202,0.0004143279,0.00005376161,0.904222,0.003141443,0.07738817,0.006048369,0.00006403838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02053255,0.0005867801,0.9757425,0.0003782438,0.00006686388,0.00006502523,0.0004228888,0.0007724909,0.001432669],"genre_scores_gemma":[0.5185577,0.00113082,0.4682284,0.0009114351,0.0001653033,0.000760861,0.001256992,0.0009033608,0.008085123],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01524231,"threshold_uncertainty_score":0.08060998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07002123007188674,"score_gpt":0.380047086270924,"score_spread":0.3100258561990372,"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."}}