CrossSCC: CrossSCC: An Single-Cell Clustering analysis framework...

In bioinformatist/GMMClassifier: What the Package Does (One Line, Title Case)

Description

CrossSCC: An Single-Cell Clustering analysis framework Crossing batches of data

CrossSCC

Usage

CrossSCC(
  m,
  markers,
  ncores = 16,
  verbose = R.utils::Verbose(threshold = -1, timestamp = TRUE),
  show.progress.bar = TRUE,
  log.file = NULL
)

Arguments

m	a matrix of single cell expression values.
markers	a dataframe contains marker information. Try examples for details.
ncores	number of CPU cores used.
verbose	verbose level. By default, CrossSCC will output all logs as well as progress bars.
show.progress.bar	Set to FALSE if you don't want to see progress bar.
log.file	a test/debug use option. Messages will be directed to this new text file instead of stderr(). Note that verbose threshold will be set to -1 with this parameter.

Value

a data.tree object.

Examples

library(data.table)
markers <- fread(system.file("extdata", "markers.csv", package = "CrossSCC"))
data(immu)
handsome.zuo <- CrossSCC(immu, markers, ncores = 16)

bioinformatist/GMMClassifier documentation built on April 24, 2020, 9:32 a.m.