KEGG and gene ontology (GO) enrichment analyses for significantly differentially expressed genes between low and high PET score groups for the terms and pathways identified in the main analyses

Meier, S; Seddon, JA; Maasdorp, E; Kleynhans, L; du Plessis, N; Loxton, AG; Malherbe, ST; Zak, DE; Thompson, E; Duffy, FJ; Kaufmann, SHE; Ottenhoff, THM; Scriba, TJ; Suliman, SORCID logo; Sutherland, JSORCID logo; Winter, J; Kuivaniemi, HORCID logo; Walzl, G and Tromp, GORCID logo (2022). KEGG and gene ontology (GO) enrichment analyses for significantly differentially expressed genes between low and high PET score groups for the terms and pathways identified in the main analyses. [Dataset]. PLOS ONE. https://doi.org/10.1371/journal.pone.0278295.s005
Copy

The analyses were performed using the topGO and kegga function from the edgeR R Bioconductor packages. The statistical metrics presented are as for S2 and S3 Tables respectively.

Keywords

Tuberculosis diagnosis and management; Neutrophils; Tuberculosis; Catalysis; Platelets; Mycobacterium tuberculosis; Gene expression; Gene ontologies

No files available. Please consult associated links.


EndNote BibTeX Reference Manager Refer Atom Dublin Core (with Type as Type) JSON Multiline CSV RDF+N-Triples OpenURL ContextObject MODS OPENAIRE Data Cite XML ASCII Citation OpenURL ContextObject in Span METS MPEG-21 DIDL RDF+XML EP3 XML RDF+N3 HTML Citation Simple Metadata
Export