Plots the results of the JackStraw analysis for PCA significance. For each PC, plots a QQ-plot comparing the distribution of p-values for all genes across each PC, compared with a uniform distribution. Also determines a p-value for the overall significance of each PC (see Details).

JackStrawPlot(
  object,
  dims = 1:5,
  cols = NULL,
  reduction = "pca",
  xmax = 0.1,
  ymax = 0.3
)

Arguments

object

Seurat object

dims

Dims to plot

cols

Vector of colors, each color corresponds to an individual PC. This may also be a single character or numeric value corresponding to a palette as specified by brewer.pal.info. By default, ggplot2 assigns colors. We also include a number of palettes from the pals package. See DiscretePalette for details.

reduction

reduction to pull jackstraw info from

xmax

X-axis maximum on each QQ plot.

ymax

Y-axis maximum on each QQ plot.

Value

A ggplot object

Details

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

See also

Author

Omri Wurtzel

Examples

data("pbmc_small")
JackStrawPlot(object = pbmc_small)
#> Warning: Removed 83 rows containing missing values or values outside the scale range
#> (`geom_point()`).