Executing clustering with tSne

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

tsneBootstrap(
  group = c("sudo", "docker"),
  scratch.folder,
  file,
  nPerm,
  permAtTime,
  percent,
  range1,
  range2,
  separator,
  logTen = 0,
  seed = 111,
  sp = 0.8,
  clusterPermErr = 0.05,
  perplexity = 10
)

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

range1,

beginning of the range of clusters to be investigated

range2,

end of the range of clusters to be investigated

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, default is 111

sp,

minimun number of percentage of cells that has to be in common in a cluster, between two permutations, default 0.8

clusterPermErr,

probability error in depicting the number of clusters in each permutation, default = 0.05

perplexity,

number of close neighbors for each point. This parameter is specific for tSne. Default value is 10. the performance of t-SNE is fairly robust under different settings of the perplexity. The most appropriate value depends on the density of your data. A larger/denser dataset requires a larger perplexity. Typical values for the perplexity range between 5 and 50

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")
tsneBootstrap(group="docker",scratch.folder="/data/scratch/",file=paste(getwd(), "bmsnkn_5x100cells.txt", sep="/"), nPerm=160, permAtTime=8, percent=10, range1=4, range2=6, separator="\t",logTen=0, seed=111, sp=0.8, clusterPermErr=0.05, perplexity=10)
}