R/SHARPBootstrap.R

In kendomaniac/rCASC: rCASC reproducible Classification Analysis of Single Cell Sequencing Data

#' @title Executing clustering with SHARP. 
#' @description This function executes a ubuntu docker that produces a specific number of permutations using SHARP as clustering tool.
#' @param group, a character string. Two options: sudo or docker, depending to which group the user belongs
#' @param scratch.folder, a character string indicating the path of the scratch folder
#' @param file, a character string indicating the path of the file, with file name and extension included
#' @param nPerm, number of permutations to be executed
#' @param permAtTime, number of permutations computed in parallel
#' @param percent, percentage of randomly selected cells removed in each permutation
#' @param separator, separator used in count file, e.g. '\\t', ','
#' @param logTen, 1 if the count matrix is already in log10, 0 otherwise
#' @param seed, important value to reproduce the same results with same input

#' @author Luca Alessandri, alessandri [dot] luca1991 [at] gmail [dot] com, University of Torino
#'
#' @return A folder Results containing a folder with the name of the experiment, which contains: VioPlot of silhouette cells value for each number of cluster used, a folder with the number of clusters used for SIMLR clustering, which contains: clusterP file with clustering results for each permutation, killedCell file with removed cells in each permutation, clustering.output a sommarize file with general information for each cells
#' @examples
#' \dontrun{
#' system("wget http://130.192.119.59/public/section4.1_examples.zip")
#' unzip("section4.1_examples.zip")
#' setwd("section4.1_examples")
#' sharpBootstrap(group="docker",scratch.folder="/data/scratch/",
#'                file=paste(getwd(), "bmsnkn_5x100cells.txt", sep="/"), 
#'                nPerm=160, permAtTime=8, percent=10, separator="\t",logTen=0, 
#'                seed=111)
#'}
#' @export

sharpBootstrap <- function(group=c("sudo","docker"), scratch.folder, file, nPerm, permAtTime, percent, separator, logTen=0, seed=111){

 
   permutationClusteringSHARP(group=group,scratch.folder=scratch.folder,file=file,nPerm=nPerm,permAtTime=permAtTime,percent=percent,separator=separator,logTen=logTen,seed=seed)
   if(separator == ","){
     matrixName=strsplit(file,"/")[[1]][length(strsplit(file,"/")[[1]])]
     matrixName <- sub(".csv$", "", matrixName)
   }else{
     matrixName=strsplit(file,"/")[[1]][length(strsplit(file,"/")[[1]])]
     matrixName <- sub(".txt$", "", matrixName)
   }
   cluster.path <- paste(data.folder=dirname(file), "Results", matrixName, sep="/")
   cluster <- as.numeric(list.dirs(cluster.path, full.names = FALSE, recursive = FALSE))
   
    if(length(cluster)==1){
       permAnalysisGriph(group=group, scratch.folder=scratch.folder, file=file,cluster,separator,sp=0.8)
    } else{
       cat("\nIt seems that there is more than one cluster folders in the output of seuratPermutation\n")
       cat("Check the results generated by clusterNgriph, and run permAnalysisGriph selecting the cluster of interest\n")
       system("echo 5 > ExitStatusFile 2>&1")
       return(5)
    }
  
}