removed makeCluster function

makeCluster function is not being used within the function and throwing an occasional error. Added the info in the help section that to use the package in windows sys one needs to use no_cores = 1.

Former-commit-id: 629970a

R/generate.celltype.data.r

@@ -5,7 +5,7 @@
 #' @param exp Numerical matrix with row for each gene and column for each cell. Row names are MGI/HGNC gene symbols. Column names are cell IDs which can be cross referenced against the annot data frame.
 #' @param annotLevels List with arrays of strings containing the cell type names associated with each column in exp
 #' @param groupName A human readable name for refering to the dataset being loaded
-#' @param no_cores Number of cores that should be used to speedup the computation
+#' @param no_cores Number of cores that should be used to speedup the computation. Use no_cores = 1 when using this package in windows system.
 #' @param savePath Directory where the CTD file should be saved
 #' @return Filenames for the saved celltype_data files
 #' @examples
@@ -32,8 +32,8 @@ generate.celltype.data <- function(exp,annotLevels,groupName,no_cores=1,savePath
 
     # Calculate the number of cores
 
-    cl <- parallel::makeCluster(no_cores)
-    print(sprintf("Using %s cores",no_cores))
+    #cl <- parallel::makeCluster(no_cores)
+    #print(sprintf("Using %s cores",no_cores))
 
     # First, check the number of annotations equals the number of columns in the expression data
     lapply(annotLevels,test <- function(x,exp){if(length(x)!=dim(exp)[2]){stop("Error: length of all annotation levels must equal the number of columns in exp matrix")}},exp)
@@ -85,7 +85,7 @@ generate.celltype.data <- function(exp,annotLevels,groupName,no_cores=1,savePath
 
     ctd3 = mclapply(ctd2,calculate.specificity.for.level,mc.cores=no_cores)
     ctd=ctd3
-    stopCluster(cl)
+    #stopCluster(cl)
 
     # Use the rank norm transformation on specificity
     rNorm <- function(ctdIN){   bbb = t(apply(ctdIN$specificity,1,RNOmni::rankNorm));  return(bbb)    }