Computational reassessment of RNA-seq data reveals key genes in active tuberculosis
Arya R, Shakya H, Chaurasia R, Kumar S, Vinetz J, Kim J. Computational reassessment of RNA-seq data reveals key genes in active tuberculosis. PLOS ONE 2024, 19: e0305582. PMID: 38935691, PMCID: PMC11210783, DOI: 10.1371/journal.pone.0305582.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkersComputational BiologyDatabases, GeneticGene Expression ProfilingGene OntologyGene Regulatory NetworksHumansProtein Interaction MapsRNA-SeqROC CurveTuberculosisConceptsMolecular Complex DetectionProtein-protein interactionsDeregulated genesGene OntologyRNA-seq dataGene Expression Omnibus (GEO) databaseIncreasing prevalence of multidrug-resistantGEO2R online toolPrevalence of multidrug resistancePathway enrichment analysisExpression levelsPatterns of variationGene expression levelsArea under curveInnate immune responseGene networksCore genesMicroarray datasetsSTRING databaseTranscript levelsEnrichment analysisGenesInterferon signalingInterferon-gamma signalingResponse to Mtb infection