Fig. 5: Effects of varying RNA:ATAC features on BC cell clustering.
From: Facilitate integrated analysis of single cell multiomic data by binarizing gene expression values
a Bar plot shows the top 25,000 HVF in the binary integrated PBMC dataset, separated to features from RNA or ATAC modalities. b Clustering accuracy with respect to the number of top HVFs (n = 21, total number of clusters). c Silhouette scores and ARIs for clusters using different numbers of HVFs. d,e UMAPs showing the 10X Multiome data from a normal mouse breast sample analyzed by our BC approach, with cells colored by BC clusters (d) or cell types (e). f, g Violin plots showing the clustering accuracies among clusters when different numbers of RNA features (f) or ATAC features (g) were included in clustering the mouse breast cells (n = 9, number of clusters). h, i UMAPs showing a human cortex 10X Multiome data analyzed by our BC approach, with cells colored by Louvain clusters (h) or the published cell types (i). j, k Violin plots showing the clustering accuracies among clusters when different numbers of RNA features (j) or ATAC features (k) were included in clustering the human cortex cells (n = 15, total number of clusters). In the boxplots, the middle line is the median while the whisker lines are 25% and 75% percentiles. Source data are provided as a Source Data file.
