`signPCA`¶

signPCA

Description¶

identify significant prinicipal components (PCs)

Usage¶

signPCA(
  gobject,
  feat_type = NULL,
  spat_unit = NULL,
  name = NULL,
  method = c("screeplot", "jackstraw"),
  expression_values = c("normalized", "scaled", "custom"),
  reduction = c("cells", "feats"),
  pca_method = c("irlba", "factominer"),
  rev = FALSE,
  feats_to_use = NULL,
  genes_to_use = NULL,
  center = T,
  scale_unit = T,
  ncp = 50,
  scree_ylim = c(0, 10),
  jack_iter = 10,
  jack_threshold = 0.01,
  jack_ylim = c(0, 1),
  verbose = TRUE,
  show_plot = NA,
  return_plot = NA,
  save_plot = NA,
  save_param = list(),
  default_save_name = "signPCA"
)

Arguments¶

Argument	Description
`gobject`	giotto object
`feat_type`	feature type
`spat_unit`	spatial unit
`name`	name of PCA object if available
`method`	method to use to identify significant PCs
`expression_values`	expression values to use
`reduction`	cells or genes
`pca_method`	which implementation to use
`rev`	do a reverse PCA
`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
`scree_ylim`	y-axis limits on scree plot
`jack_iter`	number of interations for jackstraw
`jack_threshold`	p-value threshold to call a PC significant
`jack_ylim`	y-axis limits on jackstraw plot
`verbose`	verbosity
`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¶

Two different methods can be used to assess the number of relevant or significant: prinicipal components (PC’s). list()

Screeplot works by plotting the explained variance of each individual PC in a barplot allowing you to identify which PC provides a significant contribution (a.k.a. ‘elbow method’). list()
The Jackstraw method uses the ``permutationPA` <#permutationpa>`_ function. By systematically permuting genes it identifies robust, and thus significant, PCs. list()

Value¶

ggplot object for scree method and maxtrix of p-values for jackstraw