Fig. 3

Global characterization and comparison of the LSEC and KC transcriptome and proteome datasets. a. Principal component analysis (PCA) plot displaying distinct clusters of the LSEC and KC samples in transcriptome and proteome datasets created by high-throughput mRNA sequencing (RNA-seq), and label-free proteomics (LFP). PCA plots are generated from normalized log₂ expression values (RPKM for RNA-seq, and iBAQ for LFP). b. Venn diagrams illustrating the number of gene products identified in the respective experiments (RNA-seq, LFP), and their overlap. c. Scatter plots illustrating the global correlation between the RNA-seq data and the LFP data. Results for LSECs and KCs are shown separately. d. Volcano-plot illustrating differently expressed genes. Blue dots: significantly higher expression in LSECs; red dots: significantly higher expression in KCs; gray dots: not significantly different between LSECs and KCs. Significance level: FDR ≤ 0.05 and |log₂ fold change| ≥ 1. e. Scatter plot showing correlation of KC vs. LSEC log₂ fold change values for all features expressed in both the transcriptome and proteome datasets. The r value of 0.74 indicates that approximately two thirds of the gene products are consistently significantly differentially expressed between LSECs and KCs with respect to mRNA and protein expression (FDR ≤ 0.05 and |log₂ fold change| ≥ 1)