seuratBootstrap: Executing clustering with Seurat

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

Executing clustering with Seurat

Description

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

Usage

seuratBootstrap(
  group = c("sudo", "docker"),
  scratch.folder,
  file,
  nPerm,
  permAtTime,
  percent,
  separator,
  logTen = 0,
  pcaDimensions,
  seed = 111,
  sparse = FALSE,
  format = "NULL",
  resolution = 0.6
)

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
pcaDimensions	PCs threshold selected using seuratPCAEval function.
seed	important value to reproduce the same results with same input
sparse	boolean for sparse matrix. A sparse matrix is a format that reduces the size of the matrix, considering only positions different from 0. The format supported in rCASC is the one generated by 10XGenomics output: genes.tsv, barcodes.tsv and matrix.tbx.
format	output file format csv or txt. Only required if sparse matrix is used
resolution	resolution parameter for seurat analysis default 0.8

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(s)

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

Examples

## Not run: 
system("wget http://130.192.119.59/public/section4.1_examples.zip")
unzip("section4.1_examples.zip")
setwd("section4.1_examples")
seuratBootstrap(group="docker",scratch.folder="/data/scratch/",file=paste(getwd(), "bmsnkn_5x100cells.txt", sep="/"), nPerm=160, permAtTime=8, percent=10, separator="\t",logTen=0, pcaDimensions=6, seed=111, sparse=FALSE,format="NULL")

## End(Not run)

kendomaniac/rCASC documentation built on July 3, 2024, 6:05 a.m.