{"id":"W2191643803","doi":"10.4137/cin.s21631","title":"Differential Expression Analysis for RNA-Seq: An Overview of Statistical Methods and Computational Software","year":2015,"lang":"en","type":"review","venue":"Cancer Informatics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Emergent BioSolutions (Canada)","funders":"National Cancer Institute","keywords":"DNA microarray; Computer science; Computational biology; Profiling (computer programming); Software; Data science; Identification (biology); Data mining; Gene expression profiling; Bioinformatics; Gene expression; Biology; Gene; Genetics","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":[0.005340413,0.001534504,0.002662952,0.004313739,0.000403911,0.001770841,0.00251264,0.001607587,0.003188102],"category_scores_gemma":[0.00562428,0.0008494986,0.001884058,0.005334871,0.001429468,0.001649573,0.001196943,0.004113093,0.004430068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001353821,"about_ca_system_score_gemma":0.002233855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001661435,"about_ca_topic_score_gemma":0.00172575,"domain_scores_codex":[0.9979565,0.0006243566,0.0002224794,0.0002895467,0.0008304458,0.00007656319],"domain_scores_gemma":[0.9950309,0.003693564,0.0002156563,0.0001911909,0.0007460218,0.0001227457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000527874,0.00006176059,0.0006133434,0.009542297,0.0002537488,0.0001218315,0.00009450772,0.002981598,0.005348799,0.0179891,0.03931616,0.9236241],"study_design_scores_gemma":[0.00002512432,0.0000884263,0.002022613,0.002943308,0.00018682,0.0008804663,0.00006819501,0.007270122,0.005346239,0.04563643,0.9353568,0.0001753429],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006245107,0.7459636,0.2408242,0.003252637,0.001401558,0.000138754,0.001196833,0.001795697,0.004802288],"genre_scores_gemma":[0.004188957,0.8154057,0.1711356,0.002081147,0.001504571,0.0004684817,0.001968971,0.0006811997,0.002565308],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005340413,"threshold_uncertainty_score":0.02824312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1692475521530923,"score_gpt":0.487912046175935,"score_spread":0.3186644940228427,"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."}}