R/class.R

In reggenlab/UniPath: UniPath provides robust statistical methods to represent every single cell using pathway and gene-set enrichment scores. It can be used with both single cell RNA-seq and single cell ATAC-seq profile with scalability for atlas scale data-sets. Unipath comes with several features like psuedo-temporal ordering using pathway scores and unconventional way of enumerating differences between two cell populations.

#' Finding how many times nearest neighbor of cells in each class are belonging to different cluster or class.
#'
#' @param Clusters clusters obtained from hierarchical clustering
#' @param KNN Matrix obtained from KNN function with cluster number for top nearest neighbors for each of the cell
#'
#' @return Matrix with number of times cells in same class have top k neighbors in other classes
#' @export
#'
#' @examples
#' class1()
class1 <- function(clusters,KNN,symmtery=FALSE){
  clusters = unlist(clusters)
  class1 = matrix(0,max(clusters),max(clusters))
  for (i in 1:nrow(KNN)){
    idx1 = clusters[i] ;
    for (j in 1:ncol(KNN)) {
      idx2 = KNN[i,j]
      if(symmtery==FALSE) {class1[idx1, idx2] = class1[idx1, idx2] + 1}
      if(symmtery==TRUE) {class1[idx1, idx2] = (class1[idx1, idx2] + 1) + t(class1[idx1, idx2] + 1)}

    }
  }
  return(class1)
}