I have two matrices of normalised gene expression values from single cell data from two time points. In rows I have the same genes but cells in each matrix is not same(different time point). In figure 2 C of this paper https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668937/ authors say they have calculated Pearson correlation and give one Pearson correlation coefficient for each comparison as the highest correlation coefficient.
I am using many Pearson calculation like
corrplot.mixed(cor(cbind(h_160,h_140)), order="hclust", tl.col="black") that gives me one Pearson correlation coefficient for each pair of cells (A matrix of Pearson correlation coefficient). So how I could select the highest Pearson correlation coefficient for these two matrices??