Fig. 1: Principal components analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) plots of blood-based DNA methylation data in Down syndrome (DS) and non-DS newborns.
From: The genome-wide impact of trisomy 21 on DNA methylation and its implications for hematopoiesis
PCA and t-SNE plots were generated in R, using “prcomp” and “Rtsne” functions, respectively, using genome-wide DNA methylation data from Illumina Infinium EPICmethylation Beadchip arrays in 196 DS (teal/blue) and 439 non-DS (red) newborns, excluding CpG probes on chromosomes X, Y, and 21. The first three principal components (PC1, PC2, and PC3) explained 33.2%, 10.4%, and 6.9% of the variance, respectively. a Per-sample data for PC1 plotted against PC2. b PC1 versus PC3. DS newborns with high PC1 values also had high proportions of nucleated red blood cells (nRBCs) in deconvolution analyses; this cluster of 34 DS newborns is highlighted by the blue-colored circles in both plots. PC3 appears to be related to trisomy 21 status. c First and second t-SNE dimensions for DS (teal/blue) and non-DS (red) newborns. The cluster of 34 DS newborns with high nRBC proportions is highlighted by the blue-colored circles. Two DS newborns clustered with non-DS newborns in the PCA and t-SNE plots, and these were subsequently found to be likely mosaic for trisomy 21 (see Supplementary Fig. 2).
