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.
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, ... )
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 |
Returns a Seurat object
Omri Wurtzel
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