sc3 {SC3}R Documentation

Run all steps of SC3 in one go

Description

This function is a wrapper that executes all steps of SC3 analysis in one go.

Usage

sc3.SingleCellExperiment(object, ks, gene_filter, pct_dropout_min,
  pct_dropout_max, d_region_min, d_region_max, svm_num_cells, svm_train_inds,
  svm_max, n_cores, kmeans_nstart, kmeans_iter_max, k_estimator, biology,
  rand_seed)

## S4 method for signature 'SingleCellExperiment'
sc3(object, ks = NULL, gene_filter = TRUE,
  pct_dropout_min = 10, pct_dropout_max = 90, d_region_min = 0.04,
  d_region_max = 0.07, svm_num_cells = NULL, svm_train_inds = NULL,
  svm_max = 5000, n_cores = NULL, kmeans_nstart = NULL,
  kmeans_iter_max = 1e+09, k_estimator = FALSE, biology = FALSE,
  rand_seed = 1)

Arguments

object

an object of SingleCellExperiment class.

ks

a range of the number of clusters k used for SC3 clustering. Can also be a single integer.

gene_filter

a boolen variable which defines whether to perform gene filtering before SC3 clustering.

pct_dropout_min

if gene_filter = TRUE, then genes with percent of dropouts smaller than pct_dropout_min are filtered out before clustering.

pct_dropout_max

if gene_filter = TRUE, then genes with percent of dropouts larger than pct_dropout_max are filtered out before clustering.

d_region_min

defines the minimum number of eigenvectors used for kmeans clustering as a fraction of the total number of cells. Default is 0.04. See SC3 paper for more details.

d_region_max

defines the maximum number of eigenvectors used for kmeans clustering as a fraction of the total number of cells. Default is 0.07. See SC3 paper for more details.

svm_num_cells

number of randomly selected training cells to be used for SVM prediction. The default is NULL.

svm_train_inds

a numeric vector defining indeces of training cells that should be used for SVM training. The default is NULL.

svm_max

define the maximum number of cells below which SVM is not run.

n_cores

defines the number of cores to be used on the user's machine. If not set, 'SC3' will use all but one cores of your machine.

kmeans_nstart

nstart parameter passed to kmeans function. Can be set manually. By default it is 1000 for up to 2000 cells and 50 for more than 2000 cells.

kmeans_iter_max

iter.max parameter passed to kmeans function.

k_estimator

boolean parameter, defines whether to estimate an optimal number of clusters k.

biology

boolean parameter, defines whether to compute differentially expressed genes, marker genes and cell outliers.

rand_seed

sets the seed of the random number generator. SC3 is a stochastic method, so setting the rand_seed to a fixed values can be used for reproducibility purposes.

Value

an object of SingleCellExperiment class


[Package SC3 version 1.8.0 Index]