{"id":"W3064807468","doi":"10.1101/gr.260174.119","title":"RNA-Bloom enables reference-free and reference-guided sequence assembly for single-cell transcriptomes","year":2020,"lang":"en","type":"article","venue":"Genome Research","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Canada's Michael Smith Genome Sciences Centre","funders":"National Human Genome Research Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Genome British Columbia; Genome Canada","keywords":"De novo transcriptome assembly; Transcriptome; Biology; Computational biology; Bloom filter; RNA; Gene isoform; RNA-Seq; Sequence assembly; Bloom; Reference genome; Gene; Computer science; Genetics; Gene expression; Algorithm; DNA sequencing","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":[0.005294871,0.001470534,0.001475975,0.00132307,0.001124258,0.002359505,0.001766334,0.001550592,0.001917638],"category_scores_gemma":[0.007547859,0.001072157,0.00179293,0.00127665,0.000768327,0.001658371,0.001862168,0.002042685,0.002454204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001159157,"about_ca_system_score_gemma":0.001592895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00285842,"about_ca_topic_score_gemma":0.00572157,"domain_scores_codex":[0.9971541,0.0006448823,0.0002646024,0.0008464879,0.0008952677,0.0001947356],"domain_scores_gemma":[0.9971041,0.001227325,0.0002774505,0.0006133645,0.0006411352,0.0001366159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001073604,0.0002089404,0.007731733,0.001466464,0.0003703574,0.0007333447,0.0009883922,0.1086564,0.7082883,0.01408487,0.01256714,0.1438304],"study_design_scores_gemma":[0.00008900092,0.000350335,0.003132331,0.0001492288,0.0001174441,0.0004139545,0.0002136609,0.4384076,0.5078419,0.008828546,0.0402871,0.0001689859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1020767,0.002497663,0.8582504,0.0004066854,0.000368966,0.0002463032,0.003732909,0.02791458,0.00450571],"genre_scores_gemma":[0.1593241,0.001120016,0.8194044,0.0004418283,0.0000707487,0.0004405664,0.01340682,0.003439537,0.002351945],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005294871,"threshold_uncertainty_score":0.02800232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2762866678894856,"score_gpt":0.3547813599842698,"score_spread":0.07849469209478421,"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."}}