{"id":"W4404691004","doi":"10.1093/bioinformatics/btae707","title":"<i>lefser</i>: implementation of metagenomic biomarker discovery tool, <i>LEfSe</i>, in R","year":2024,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Population and Public Health","funders":"National Cancer Institute; National Institutes of Health","keywords":"Bioconductor; Python (programming language); Metagenomics; Computer science; Software; Data mining; Source code; JavaScript; Benchmarking; Visualization; Population; Data science; Biology; World Wide Web; 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":[0.00604694,0.003415797,0.002184723,0.003097451,0.001236068,0.003903711,0.005227892,0.001297203,0.09271686],"category_scores_gemma":[0.01982482,0.001703132,0.002860114,0.002210006,0.001174666,0.003035494,0.003340206,0.003924298,0.1035517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135782,"about_ca_system_score_gemma":0.003392357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003418036,"about_ca_topic_score_gemma":0.004702939,"domain_scores_codex":[0.9973897,0.0005228624,0.0002680052,0.000853169,0.0007079424,0.0002583796],"domain_scores_gemma":[0.9941309,0.002470071,0.0007776475,0.001132632,0.001029753,0.0004589648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004483049,0.00006096698,0.003966844,0.00160351,0.0004476337,0.0003240074,0.000291388,0.00386189,0.009196633,0.005711174,0.911528,0.06255966],"study_design_scores_gemma":[0.0006542514,0.0002461855,0.007756165,0.0005629672,0.0003008086,0.001354687,0.0001462513,0.07009154,0.05278894,0.05541155,0.8101044,0.0005822624],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.002299847,0.0004021677,0.2528439,0.001130114,0.0004811842,0.0003867692,0.1054187,0.6314191,0.005618281],"genre_scores_gemma":[0.03614552,0.0005086362,0.477006,0.002606605,0.0003310319,0.00335671,0.1725359,0.296353,0.01115659],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.09271686,"threshold_uncertainty_score":0.3101688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01587551541960474,"score_gpt":0.2952289495447525,"score_spread":0.2793534341251478,"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."}}