Fig. 5

The dramatic change of bone marrow microenvironment in a CLL patient versus a healthy donor. a UMAP visualization for joint clustering of human BMMC scRNA-seq (5k cells) and scATAC-seq (9k cells) from the CLL patient and the healthy donor. Colors represent the cells from different technologies. The cells are joined by CCA on gene expression level and regulatory potential from MAESTRO. b UMAP visualization for joint clustering of human BMMC scRNA-seq (5k cells) and scATAC-seq (9k cells) from the CLL patient and the healthy donor. The cells are joined by CCA on gene expression level and regulatory potential from MAESTRO. Colors represent the cell types, which are generated using the scRNA-seq dataset and transferred to the scATAC-seq dataset. c Cell-type proportions of the CLL patient and the healthy donor. The total number of cells in each sample (CLL patients or healthy donors) should add up to 1. The scRNA-seq and scATAC-seq are quantified separately. Statistic significance is evaluated using two proportion z test, ***p < 2.2e−16, *p ≤ 0.05, ^N.S.p > 0.05. d The rank of driver regulators in CLL1 (left) and CLL2 (right) cluster of the BMMC dataset. The x-axis represents the TF enrichment score from LISA result on differentially expressed genes between CLL1 and CLL2 clusters in scRNA-seq; the y-axis represents the TF enrichment score from GIGGLE result on differential peaks between CLL1 and CLL2 clusters in scATAC-seq. The color of the circles represents the averaged expression level of regulators in corresponding clusters of scRNA-seq, and the size represents the TF enrichment score using GIGGLE in corresponding clusters of scATAC-seq. The names of the top 10 TFs from LISA and GIGGLE are labeled on the graph