Fig. 1 | Nature Communications

Fig. 1

From: Pan-cancer analysis of transcriptional metabolic dysregulation using The Cancer Genome Atlas

Fig. 1

Transcriptional metabolic pathway analysis methods pipeline. a Twenty-six cohorts of tumor samples, including two pooled sets (COADREAD and LUNG) from The Cancer Genome Atlas (TCGA), with matched normal samples, were utilized to determine the transcriptional metabolic profiles specific to each type of cancer, as compared to their normal. b Pathway scores ((Σlog FC* − log(adj.p.val))/√n), for 114 metabolic pathways from KEGG, were then calculated based on the results of differential expressed gene (DEG) analysis using Limma to compare tumors to matched normal. Pathways are then bootstrapped for significance, to determine which pathways are highly dysregulated as compared to chance. Those pathways are then plotted in a heatmap, with the type of cancer as the x-axis and the 114 pathways as the y-axis. Non-significant pathways are gray and a gradient from white to red for those pathways significantly dysregulated and the intensity of red indicating the magnitude of dysregulation. c The number of significant pathway scores are then summed to determine which types of cancers are most metabolically dysregulated at the transcriptional level, as compared to the average number of dysregulated pathways (dashed line). d The pathways were then sorted into each of the 10 major metabolic pathway subtypes defined by KEGG and later underwent e master regulator analysis via iRegulon

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