deepClustering: deepClustering

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

deepClustering

Description

The present function compress data using autoencoder partially connected

Usage

deepClustering(
  group = c("sudo", "docker"),
  scratch.folder,
  file,
  separator,
  nCluster,
  bias,
  finetune_iters = 1e+05,
  nEpochs = 50000,
  seed = 1111,
  projectName,
  bN = "NULL"
)

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
separator	separator used in count file, e.g. '\t', ','
nCluster	number of cluster in which the dataset is divided
bias	bias method to use : "mirna" , "TF", "CUSTOM", kinasi,immunoSignature, cytoBands, ALL
finetune_iters	number of deep iteration
nEpochs	number of Epochs for neural network training
seed	important value to reproduce the same results with same input
projectName	might be different from the matrixname in order to perform different analysis on the same dataset
bN	name of the custom bias file. This file need header, in the first column has to be the source and in the second column the gene symbol. All path needs to be provided.

Author(s)

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

Examples

## Not run: 
deepClustering(group=c("docker"), scratch.folder="/scratch/", file="/home/lucastormreig/clustering_autoencoder/DCA/Rfunction/setA2.csv",separator=",", nCluster=5, bias="TF", finetune_iters=3, nEpochs=2,seed=1111,projectName="TF",bN="NULL")

## End(Not run)

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