{"id":"W2160164696","doi":"10.1038/nmeth.1503","title":"Alternative expression analysis by RNA sequencing","year":2010,"lang":"en","type":"article","venue":"Nature Methods","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":314,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"Canadian Institutes of Health Research","keywords":"Biology; Alternative splicing; Exon; Intron; Computational biology; RNA splicing; RNA-Seq; RNA; Sanger sequencing; Massive parallel sequencing; DNA microarray; Transcriptome; DNA sequencing; Gene expression; Genetics; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004127214,0.00009551301,0.0001105647,0.0000549483,0.00007070387,0.00002084245,0.0001928533,0.0003304762,0.00008416562],"category_scores_gemma":[0.0001498566,0.0000778798,0.0001118128,0.0002193341,0.00003642012,0.000003153157,0.00004617819,0.0004025765,0.000001920103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001179582,"about_ca_system_score_gemma":0.00003400234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002253366,"about_ca_topic_score_gemma":0.00001514961,"domain_scores_codex":[0.9992555,0.0001254006,0.0001061439,0.0002949122,0.00009444803,0.0001235591],"domain_scores_gemma":[0.9993553,0.00002050749,0.00007204535,0.0004034484,0.00009158604,0.0000570933],"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":[0.000008329433,0.000009192284,0.0001672073,0.000001449678,0.00009099697,2.417661e-7,0.00002164335,0.00004097327,0.9817648,0.0001415083,0.002876442,0.01487722],"study_design_scores_gemma":[0.00008960595,0.00001505987,0.0002443216,0.000001400043,0.00005864081,8.083205e-7,0.00001763313,0.0003517371,0.9149674,0.0002215504,0.08393461,0.00009722276],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.537711,0.001967994,0.4547031,0.0001235629,0.0004976466,0.00008094062,0.00003294123,0.00001338678,0.004869408],"genre_scores_gemma":[0.8037959,0.00007374942,0.1942252,0.0002752163,0.0002905697,0.00001850206,0.000103402,0.00001059066,0.001206845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2660849,"threshold_uncertainty_score":0.3175846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168446721525045,"score_gpt":0.3798137378372237,"score_spread":0.3681292706219733,"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."}}