{"id":"W3134842602","doi":"10.2217/epi-2020-0344","title":"Detecting Differentially Methylated Regions with Multiple Distinct Associations","year":2021,"lang":"en","type":"article","venue":"Epigenomics","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Nursing Research; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institute of Environmental Health Sciences; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Diabète Québec; National Institutes of Health; National Institute of General Medical Sciences; American Diabetes Association","keywords":"Biology; CpG site; Type I and type II errors; Statistical power; Computational biology; Differentially methylated regions; DNA methylation; Statistics; Bioinformatics; Genetics; Computer science; Evolutionary biology; Gene; Mathematics; Gene expression","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":[0.0001419734,0.0001364258,0.0001398864,0.00002766387,0.0002234015,0.00004971852,0.00009754056,0.0001293723,0.00001492405],"category_scores_gemma":[0.0003389727,0.0001335667,0.00008025453,0.0001323206,0.00003164991,0.000002876151,0.00008016267,0.0001033025,0.000007308791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003456107,"about_ca_system_score_gemma":0.0001411202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003457476,"about_ca_topic_score_gemma":0.001429462,"domain_scores_codex":[0.9990457,0.00009220075,0.0002057737,0.0003271844,0.0001024432,0.0002266564],"domain_scores_gemma":[0.9992176,0.00005261428,0.0001262451,0.0003318123,0.0001916499,0.00008008187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003047735,0.00007639685,0.05014269,0.000006127245,0.0001342897,0.000007678637,0.0001079774,0.0006607758,0.9456914,0.0001138281,0.00003190447,0.002996455],"study_design_scores_gemma":[0.0006680863,0.0001278353,0.1131368,0.000008207987,0.00006332323,0.000004541253,0.00008801891,0.0004029529,0.8748244,0.0004932277,0.009876506,0.0003061634],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9337395,0.0008036507,0.06396322,0.0001170676,0.0001303925,0.0001056065,0.00004581639,0.00002068642,0.001074102],"genre_scores_gemma":[0.9921213,0.0001650926,0.006148932,0.00004090886,0.0001863944,0.00001135595,0.0005941282,0.00003453876,0.0006973646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07086702,"threshold_uncertainty_score":0.5446694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506899165380337,"score_gpt":0.2430397883676819,"score_spread":0.2279707967138785,"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."}}