Figure 6.
Differential gene expression may guide clinical diagnosis. (A) Consensus clustering heatmap of expression values (Z score; mean centered and divided by standard deviation) (k = 2 through k = 10). Rows are first split by their WGCNA module membership and then clustered by expression values. The module number is on the left, and the corresponding color is on the right. Heatmap columns were clustered by consensus clustering (k = 7). (B) The barplot demonstrates the gene mutation frequencies colored by the consensus clustering result. (C) Heatmap summary of Pearson correlations of the WGCNA module eigengenes and the numeric clinical variables. The y-axis indicates the clinical variables with the number of samples used in the correlation shown as n. The x-axis indicates the module name/color. Note that the survival data are only limited to samples with noncensored data. HCT, hematocrit; MCV, mean corpuscular volume.

Differential gene expression may guide clinical diagnosis. (A) Consensus clustering heatmap of expression values (Z score; mean centered and divided by standard deviation) (k = 2 through k = 10). Rows are first split by their WGCNA module membership and then clustered by expression values. The module number is on the left, and the corresponding color is on the right. Heatmap columns were clustered by consensus clustering (k = 7). (B) The barplot demonstrates the gene mutation frequencies colored by the consensus clustering result. (C) Heatmap summary of Pearson correlations of the WGCNA module eigengenes and the numeric clinical variables. The y-axis indicates the clinical variables with the number of samples used in the correlation shown as n. The x-axis indicates the module name/color. Note that the survival data are only limited to samples with noncensored data. HCT, hematocrit; MCV, mean corpuscular volume.

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