Gene signature discovery and systematic validation across diverse clinical cohorts for TB prognosis and response to treatment
Fig 2
Network analysis results and gene signature.
(A–D) Network degree distribution fitting. The distribution of weighted degrees for each network was fit with a probability density function to help determine top–ranked genes to retain for the candidate gene set (Methods). (E) Overlap of top 5% of genes by weighted degree in each network. (F) Gene signature mapped on protein–protein interaction network. Protein–protein association network of 45 candidate genes constructed with STRING. Width of edge corresponds to edge confidence. Associations correspond to physical interactions or represent proteins that act functionally together. (G) A visualization of S2 Table, showcasing which pathways (and corresponding genes) were enriched for our 45–gene set (red: gene is in pathway, blue: gene is not part of pathway). (H–K) Volcano plots displaying the mean log2(Fold Change) of gene expression across cohorts against the weighted degree for each network for all genes within each network. Forty–five candidate genes highlighted in orange within each plot. (L–O) Heatmaps of log2(Fold Change) for each of the 45 candidate genes (rows) between disease conditions displayed for each cohort (columns) that were used in constructing each network. The corresponding GSE ID of each cohort was labeled on columns. If a cohort contains multiple clinically defined populations, a specific comparison is also highlighted on the column. Bolded gene names are genes that are also included in the reduced model, genes with an asterisk are not included in either the full or reduced model.