Fig. 2
From: Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
Benchmarking scvis against t-SNE on synthetic data. a The original 2200 two-dimensional synthetic data points (points are colored by cluster labels. The randomly distributed outliers are also colored in a distinct color, same for b, c), b t-SNE results on the transformed nine-dimensional dataset with default perplexity parameter of 30, c scvis results, d coloring points based on their log-likelihoods from scvis, e the kernel density estimates of the scvis results, where the density contours are represented by lines, f average K-nearest neighbor preservations across ten runs for different Ks, and g the average K-nearest neighbor preservations (K = 10) for different numbers of subsampled data points from ten repeated runs. The numbers at the top are the adjusted p-values (FDR, one-sided Welch’s t-test) comparing the average Knn preservations from scvis with those from t-SNE. Boxplots in f, g denote the medians and the interquartile ranges (IQRs). The whiskers of a boxplot are the lowest datum still within 1.5 IQR of the lower quartile and the highest datum still within 1.5 IQR of the upper quartile
