`R/generics.R`

, `R/dimensional_reduction.R`

`ScoreJackStraw.Rd`

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

`JackStrawPlot`

after running ScoreJackStraw.

Returns a Seurat object