Supplementary Figure 3: Principal component analysis (PCA) shows important sources of variability in the transcriptome.
From: Transcriptome networks identify mechanisms of viral and nonviral asthma exacerbations in children
PCA was performed on the expression data and principal components (PCs) were correlated to clinical and demographic variables. To determine significance, Pearson correlation was calculated for continuous variables and ANOVA was run for categorical variables. Significant relationships (FDR<0.05) between variables and PCs show a circle on the heatmap to indicate magnitude of the relationship, where color represents magnitude and direction of Pearson correlation for continuous variables and darkness of gray represents the magnitude of R2 from ANOVA for categorical variables. Variables that do not have a significant relationship with PCs show the FDR value in their square on the heatmap. (a) Association heatmaps of variables for nasal samples. (b) Association heatmaps of variables for blood samples.
