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Seurat (version 5.0.3)

VST: Variance Stabilizing Transformation

Description

Apply variance stabilizing transformation for selection of variable features

Usage

VST(data, margin = 1L, nselect = 2000L, span = 0.3, clip = NULL, ...)
# S3 method for default
VST(data, margin = 1L, nselect = 2000L, span = 0.3, clip = NULL, ...)
# S3 method for IterableMatrix
VST(
  data,
  margin = 1L,
  nselect = 2000L,
  span = 0.3,
  clip = NULL,
  verbose = TRUE,
  ...
)
# S3 method for dgCMatrix
VST(
  data,
  margin = 1L,
  nselect = 2000L,
  span = 0.3,
  clip = NULL,
  verbose = TRUE,
  ...
)
# S3 method for matrix
VST(data, margin = 1L, nselect = 2000L, span = 0.3, clip = NULL, ...)

Value

A data frame with the following columns:

  • “mean”: ...

  • “variance”: ...

  • “variance.expected”: ...

  • “variance.standardized”: ...

  • “variable”: TRUE if the feature selected as variable, otherwise FALSE

  • “rank”: If the feature is selected as variable, then how it compares to other variable features with lower ranks as more variable; otherwise, NA

Arguments

data

A matrix-like object

margin

Unused

nselect

Number of of features to select

span

the parameter \(\alpha\) which controls the degree of smoothing.

clip

Upper bound for values post-standardization; defaults to the square root of the number of cells

...

Arguments passed to other methods

verbose

...