clustermap.R

clusterMap <- function(sce1, sce2) {
  
  clusters1 <- sort(unique(sce1$cluster)) # get unique clusters
  clusters2 <- sort(unique(sce2$cluster))
  
  # Check this is gene (row) by cluster (cell) - if not needs transposed
  cluster_means_1 <- sapply(clusters1, function(x) { 
    rowMeans(as.matrix(logcounts(sce1[,sce1$cluster == x]))
  }))
  
  cluster_means_2 <- sapply(clusters2, function(x) { 
    rowMeans(as.matrix(logcounts(sce2[,sce2$cluster == x]))
  }))

 # The cor function can take two matrices and return
 # the correlations between their columns
 cor(cluster_means_1, cluster_means_2)
}