BCscTool

The present function associates the clusters of two different and indipendent experiments using the Bray Curtis dissimilarity. BOTH set must have same number and name of ROW (GENES)

BCscTool(
  group = c("sudo", "docker"),
  scratch.folder,
  setA,
  setAclustering,
  markerA,
  setB,
  setBclustering,
  markerB,
  separator,
  contamination = 5,
  permutation = 50,
  threshold = 3
)

Arguments

group,

a character string. Two options: sudo or docker, depending to which group the user belongs

scratch.folder,

a character string indicating the path of the scratch folder

setA,

path to the first dataset

setAclustering,

path to the clustering file for the first dataset. This file is derived from clustering.output file generated by the rCASC clustering. It contains the following columns: CellName, Belonging_Cluster

markerA,

path to the file containing cluster specific genes for the first dataset. The file requires the following column: gene, cluster

setB,

path to the second dataset

setBclustering,

path to the clustering file for the second dataset. This file is derived from clustering.output file generated by the rCASC clustering. It contains the following columns: CellName, Belonging_Cluster

markerB,

path to the file containing cluster specific genes for the second dataset. The file requires the following column: gene, cluster

separator,

separator used in both count file, e.g. ','

contamination,

fraction of genes to be contaminated at each eprmutaitone DEFAULT VALUE: 5

permutation,

number of permutations DEFAULT VALUE: 50

threshold,

minimum value to consider a gene expressed in both count sets. DEFAULT VALUE: 3

Author

Gabriele Piacenti, g [dot] pia91 [at] gmail [dot] com, University of Torino

Examples

    
if (FALSE) {
BCscTool(group = "docker",
         scratch.folder = "/home/user09/piacenti/ProvaBCSC/scratch",
         setA = paste(getwd(),"setA.csv",sep = "/"),
         setAclustering = paste(getwd(),"setA_clustering.csv",sep = "/"),
         markerA = paste(getwd(),"setA.markers.csv",sep = "/"),
         setB =paste(getwd(),"set1.csv",sep = "/"),
         setBclustering = paste(getwd(),"set1_clustering.csv",sep = "/"),
         markerB =paste(getwd(),"set1.markersPROVA.csv",sep = "/"),
         separator =",",
         contamination = 10 ,
         permutation = 10,
         threshold = 3 )
}