`tsneBootstrap.Rd`

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 )

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

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

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) }