{"id":"W2060064237","doi":"10.1186/1471-2105-12-139","title":"PeakRanger: A cloud-enabled peak caller for ChIP-seq data","year":2011,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"National Science Foundation","keywords":"Computer science; Cloud computing; Chromatin immunoprecipitation; Massively parallel; Software; Chip; Parallel computing; Multi-core processor; Data mining; Biology; Operating system","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005245787,0.002557824,0.001697603,0.00302675,0.001336204,0.002228234,0.005279466,0.001614477,0.02074265],"category_scores_gemma":[0.009493588,0.001509896,0.002006672,0.002666469,0.0008220103,0.001851513,0.002127761,0.002978721,0.01506317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001395949,"about_ca_system_score_gemma":0.002470748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004605203,"about_ca_topic_score_gemma":0.005925868,"domain_scores_codex":[0.9961133,0.0004167169,0.000277362,0.00117692,0.001707293,0.0003083659],"domain_scores_gemma":[0.9946576,0.002273386,0.0005946857,0.0008802428,0.001237865,0.0003562501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005484753,0.0005855516,0.01836376,0.003564708,0.001231947,0.000942956,0.0009219201,0.03627029,0.1325938,0.007650479,0.5410562,0.2513337],"study_design_scores_gemma":[0.001718452,0.0004904112,0.0181864,0.0003654238,0.000381819,0.00117622,0.0002276724,0.5184122,0.2366752,0.01824094,0.2030505,0.001074655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01375821,0.001059134,0.3303536,0.0004698564,0.0003919854,0.0007293682,0.05720231,0.5906298,0.005405756],"genre_scores_gemma":[0.07791672,0.0006241211,0.7509269,0.001815147,0.0002520653,0.002423921,0.09783971,0.0636522,0.004549214],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02074265,"threshold_uncertainty_score":0.06939107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05121050092748334,"score_gpt":0.2519177744359786,"score_spread":0.2007072735084953,"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."}}