{"id":"W4379230391","doi":"10.3390/biology12060812","title":"RNA Sequencing of Pooled Samples Effectively Identifies Differentially Expressed Genes","year":2023,"lang":"en","type":"article","venue":"Biology","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Van Andel Research Institute","keywords":"Biology; RNA; Gene; Genetics; RNA-Seq; Deep sequencing; Mutant; DNA sequencing; Computational biology; Genome; Gene expression; Transcriptome","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001929575,0.001186957,0.001277309,0.001455282,0.0006578352,0.001107584,0.0005302924,0.0009991713,0.001767502],"category_scores_gemma":[0.003671298,0.000530112,0.001078771,0.001046846,0.0006694213,0.0004790741,0.0006154146,0.00127856,0.001093327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003717149,"about_ca_system_score_gemma":0.0007222982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004044252,"about_ca_topic_score_gemma":0.001871922,"domain_scores_codex":[0.9974892,0.0003744028,0.000243356,0.00106426,0.0006834951,0.0001452724],"domain_scores_gemma":[0.9967595,0.001435001,0.0004975229,0.0005145752,0.00068967,0.0001037861],"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":[0.0001220195,0.00003939505,0.0005323312,0.0001526925,0.00005817194,0.00005337154,0.00004528405,0.0001929625,0.9940916,0.0001046445,0.0001654426,0.004442071],"study_design_scores_gemma":[0.00007464824,0.000683374,0.01799734,0.00007873635,0.0003788066,0.0003788887,0.0001240106,0.006224563,0.9612122,0.001299719,0.01149144,0.00005638061],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4330074,0.004206905,0.5348862,0.0006372143,0.001059264,0.001712568,0.01654054,0.003137352,0.004812472],"genre_scores_gemma":[0.3656402,0.003454215,0.5941981,0.001954513,0.0005669679,0.003800222,0.02439646,0.001326364,0.004662876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001929575,"threshold_uncertainty_score":0.01020473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02552522549216982,"score_gpt":0.2628887424395615,"score_spread":0.2373635169473916,"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."}}