jackstrawPlot: jackstrawPlot

In drieslab/Giotto_site_suite: Spatial Single-Cell Transcriptomics Toolbox

jackstrawPlot

Description

identify significant prinicipal components (PCs)

Usage

jackstrawPlot(
  gobject,
  spat_unit = NULL,
  feat_type = NULL,
  expression_values = c("normalized", "scaled", "custom"),
  reduction = c("cells", "feats"),
  feats_to_use = NULL,
  genes_to_use = NULL,
  center = FALSE,
  scale_unit = FALSE,
  ncp = 20,
  ylim = c(0, 1),
  iter = 10,
  threshold = 0.01,
  verbose = TRUE,
  show_plot = NA,
  return_plot = NA,
  save_plot = NA,
  save_param = list(),
  default_save_name = "jackstrawPlot"
)

Arguments

gobject	giotto object
spat_unit	spatial unit
feat_type	feature type
expression_values	expression values to use
reduction	cells or genes
feats_to_use	subset of features to use for PCA
genes_to_use	deprecated, use feats_to_use
center	center data before PCA
scale_unit	scale features before PCA
ncp	number of principal components to calculate
ylim	y-axis limits on jackstraw plot
iter	number of interations for jackstraw
threshold	p-value threshold to call a PC significant
verbose	show progress of jackstraw method
show_plot	show plot
return_plot	return ggplot object
save_plot	directly save the plot [boolean]
save_param	list of saving parameters from all_plots_save_function()
default_save_name	default save name for saving, don't change, change save_name in save_param

Details

The Jackstraw method uses the permutationPA function. By systematically permuting genes it identifies robust, and thus significant, PCs.

Value

ggplot object for jackstraw method

drieslab/Giotto_site_suite documentation built on April 26, 2023, 11:51 p.m.