Spatial quantile normalization removes the mean-correlation relationship.

Same data as Fig 2, but after applying spatial quantile normalization (SpQN). (a) Like Fig 3a, i.e. densities of the Pearson correlation between all genes within each of 10 expression bins (background) as well as the top 0.1% correlations (possible signal). (b) Like Fig 2b, i.e. IQRs of Pearson correlations between genes in each of 10 different expression levels. (c) Like Fig 2c, i.e. the relationship between IQR of gene-gene correlation distribution and the lowest of the two expression bins associated with the submatrix. (d) Like Fig 3b, i.e. the expression level of pairs of genes in different subsets (all genes (black), genes above the 0.1% threshold with (orange) and without SpQN (gray)).