{"id":"W3186869997","doi":"10.1101/2021.07.17.452734","title":"Genome-Wide Detection of Imprinted Differentially Methylated Regions Using Nanopore Sequencing","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic Syndromes and Imprinting","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"University of British Columbia; Canada Research Chairs","keywords":"Genomic imprinting; Imprinting (psychology); Differentially methylated regions; Biology; DNA methylation; Nanopore sequencing; Genetics; Methylated DNA immunoprecipitation; CpG site; Genome; Computational biology; Epigenetics; Germline; Methylation; Gene; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002819179,0.0001802441,0.0002047424,0.0004271059,0.0001342663,0.0002867945,0.0002287218,0.0004079088,0.0008317136],"category_scores_gemma":[0.0004325366,0.0001359431,0.0001820325,0.0002548044,0.0001929324,0.0001439482,0.0003684128,0.0003622335,0.0003124889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001701295,"about_ca_system_score_gemma":0.00009268714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006284203,"about_ca_topic_score_gemma":0.001425222,"domain_scores_codex":[0.9997438,0.00003421491,0.00001024375,0.0001172295,0.00007109583,0.00002335698],"domain_scores_gemma":[0.9997405,0.0001081835,0.00005548247,0.00004289741,0.00002778963,0.00002507796],"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":[0.00006629035,0.00001164308,0.004609596,0.0000296557,0.00003057934,0.00004422135,0.00002886988,0.0004670897,0.9887583,0.0001963283,0.0001489786,0.005608493],"study_design_scores_gemma":[0.00001227175,0.0001178759,0.05746168,0.00001093612,0.00005451846,0.0004809991,0.00005491828,0.01097484,0.923604,0.0008720686,0.006336027,0.00001995196],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9201434,0.001043798,0.07025296,0.0001852819,0.00004091975,0.00003545107,0.005530057,0.000681494,0.002086597],"genre_scores_gemma":[0.9196911,0.0004165505,0.0727485,0.0001814458,0.0000191414,0.00005359447,0.004774075,0.00009147418,0.00202404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008317136,"threshold_uncertainty_score":0.002782404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622853756588703,"score_gpt":0.2219647045147862,"score_spread":0.2057361669488992,"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."}}