{"id":"W3126924910","doi":"10.1101/2021.02.05.429923","title":"Analysis of mitochondrial genome methylation using Nanopore single-molecule sequencing","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds National de la Recherche Luxembourg; Deutsche Forschungsgemeinschaft; Joachim Herz Stiftung; Canadian Institutes of Health Research; Alexander von Humboldt-Stiftung","keywords":"DNA methylation; Nanopore sequencing; Biology; Mitochondrial DNA; Methylation; Bisulfite sequencing; CpG site; Illumina Methylation Assay; Genetics; DNA sequencing; Computational biology; Bisulfite; Genome; DNA; Molecular biology; Gene; Gene expression","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":[0.0004892008,0.0002918444,0.0003461815,0.0004104136,0.0002468659,0.0003502136,0.0003323941,0.0005405704,0.001126977],"category_scores_gemma":[0.000825101,0.00017555,0.0002551326,0.0002165197,0.0002580359,0.0002970338,0.0003289588,0.0005607097,0.0005445757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002423343,"about_ca_system_score_gemma":0.0001661243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007000707,"about_ca_topic_score_gemma":0.001136203,"domain_scores_codex":[0.9996781,0.00005230937,0.00001813889,0.0001282911,0.00009402003,0.00002911604],"domain_scores_gemma":[0.9995524,0.0001737393,0.00006767341,0.00007068067,0.00009168401,0.00004378121],"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":[0.00005655979,0.00000884992,0.00090792,0.00005452385,0.00001948756,0.0000235457,0.00002988612,0.0003417545,0.9945117,0.0001272405,0.00008657102,0.003831936],"study_design_scores_gemma":[0.00000486918,0.00008623672,0.009048163,0.00001305374,0.0000325819,0.0001343604,0.00002655306,0.009317772,0.9778064,0.0004268874,0.003085091,0.00001793363],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7638014,0.0020956,0.2246696,0.0002884019,0.0001251996,0.0001249314,0.005093247,0.001731956,0.002069694],"genre_scores_gemma":[0.7956643,0.0009609205,0.1948023,0.000268793,0.00003569687,0.0001534918,0.004698042,0.0002953373,0.003121058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001126977,"threshold_uncertainty_score":0.003770113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02306164818760325,"score_gpt":0.2461748140173402,"score_spread":0.2231131658297369,"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."}}