Compute Jackstraw scores significance.

Significant PCs should show a p-value distribution that is strongly skewed to the left compared to the null distribution. The p-value for each PC is based on a proportion test comparing the number of features with a p-value below a particular threshold (score.thresh), compared with the proportion of features expected under a uniform distribution of p-values.

Usage

ScoreJackStraw(object, ...)

# S3 method for class 'JackStrawData'
ScoreJackStraw(object, dims = 1:5, score.thresh = 1e-05, ...)

# S3 method for class 'DimReduc'
ScoreJackStraw(object, dims = 1:5, score.thresh = 1e-05, ...)

# S3 method for class 'Seurat'
ScoreJackStraw(
  object,
  reduction = "pca",
  dims = 1:5,
  score.thresh = 1e-05,
  do.plot = FALSE,
  ...
)

Arguments

object

An object

...

Arguments passed to other methods

dims

Which dimensions to examine

score.thresh

Threshold to use for the proportion test of PC significance (see Details)

reduction

Reduction associated with JackStraw to score

do.plot

Show plot. To return ggplot object, use JackStrawPlot after running ScoreJackStraw.

Value

Returns a Seurat object

See also

JackStrawPlot

JackStrawPlot

Author

Omri Wurtzel