runSeuratFindHVG: runSeuratFindHVG Find highly variable genes and store in the...

In compbiomed/singleCellTK: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

runSeuratFindHVG Find highly variable genes and store in the input sce object

Description

runSeuratFindHVG Find highly variable genes and store in the input sce object

Usage

runSeuratFindHVG(
  inSCE,
  useAssay = "counts",
  method = c("vst", "dispersion", "mean.var.plot"),
  hvgNumber = 2000,
  createFeatureSubset = "hvf",
  altExp = FALSE,
  verbose = TRUE
)

Arguments

inSCE	(sce) object to compute highly variable genes from and to store back to it
useAssay	Specify the name of the assay to use for computation of variable genes. It is recommended to use a raw counts assay with the "vst" method and normalized assay with all other methods. Default is "counts".
method	selected method to use for computation of highly variable genes. One of 'vst', 'dispersion', or 'mean.var.plot'. Default "vst" which uses the raw counts. All other methods use normalized counts.
hvgNumber	numeric value of how many genes to select as highly variable. Default 2000
createFeatureSubset	Specify a name of the subset to create for the identified variable features. Default is "hvf". Leave it NULL if you do not want to create a subset of variable features.
altExp	Logical value indicating if the input object is an altExperiment. Default FALSE.
verbose	Logical value indicating if informative messages should be displayed. Default is TRUE.

Value

Updated SingleCellExperiment object with highly variable genes computation stored

See Also

runFeatureSelection, runModelGeneVar, getTopHVG, plotTopHVG

Examples

data(scExample, package = "singleCellTK")
sce <- runSeuratFindHVG(sce)

compbiomed/singleCellTK documentation built on Oct. 27, 2024, 3:26 a.m.