Executing clustering with SHARP.

This function executes a ubuntu docker that produces a specific number of permutations using SHARP as clustering tool.

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

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

file,

a character string indicating the path of the file, with file name and extension included

nPerm,

number of permutations to be executed

permAtTime,

number of permutations computed in parallel

percent,

percentage of randomly selected cells removed in each permutation

separator,

separator used in count file, e.g. '\t', ','

logTen,

1 if the count matrix is already in log10, 0 otherwise

seed,

important value to reproduce the same results with same input

Value

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

Author

Luca Alessandri, alessandri [dot] luca1991 [at] gmail [dot] com, University of Torino

Examples

if (FALSE) {
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)
}