{"id":"W2802080790","doi":"10.1038/s41598-018-25022-6","title":"DNAp: A Pipeline for DNA-seq Data Analysis","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Environmental Health Sciences; National Institute of General Medical Sciences; U.S. National Library of Medicine; U.S. Food and Drug Administration; Hamilton Health Sciences Foundation; National Science Foundation","keywords":"Pipeline (software); Computer science; Documentation; Exome sequencing; Software; DNA sequencing; Exome; Computational biology; Data mining; Mutation; Biology; Genetics; DNA; Gene; Operating system","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":[0.006546887,0.004380525,0.002141169,0.004895725,0.002019091,0.003068616,0.003785972,0.001639819,0.04423611],"category_scores_gemma":[0.01045871,0.003349067,0.003438923,0.003633152,0.001050147,0.002389262,0.003807056,0.005326021,0.04031606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001660029,"about_ca_system_score_gemma":0.00535486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00545966,"about_ca_topic_score_gemma":0.007131604,"domain_scores_codex":[0.9964499,0.0006436392,0.0004621946,0.001219259,0.000912566,0.0003124217],"domain_scores_gemma":[0.9965521,0.00146661,0.0003286262,0.0006076844,0.0007392991,0.0003057608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001608132,0.0002027642,0.004122655,0.003756509,0.00113328,0.0008187746,0.0008545778,0.009214633,0.07892651,0.006619138,0.7063165,0.1864265],"study_design_scores_gemma":[0.001214647,0.0003441754,0.007414009,0.0004087935,0.0004388346,0.001078825,0.0002479059,0.1116279,0.123316,0.04265823,0.7103823,0.0008684788],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.002444809,0.000530151,0.5413077,0.0005302091,0.0004427664,0.001216605,0.1188885,0.3308151,0.003824205],"genre_scores_gemma":[0.0128658,0.0005187256,0.7546058,0.001191736,0.0001453481,0.005087847,0.1726217,0.04629592,0.006667162],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04423611,"threshold_uncertainty_score":0.1479846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02573596516031558,"score_gpt":0.3005871940490115,"score_spread":0.274851228888696,"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."}}