screePlot: screePlot

View source: R/dimension_reduction.R

screePlotR Documentation

screePlot

Description

identify significant principal components (PCs) using an screeplot (a.k.a. elbowplot)

Usage

screePlot(
  gobject,
  spat_unit = NULL,
  feat_type = NULL,
  name = NULL,
  expression_values = c("normalized", "scaled", "custom"),
  reduction = c("cells", "feats"),
  method = c("irlba", "exact", "random", "factominer"),
  rev = FALSE,
  feats_to_use = NULL,
  genes_to_use = NULL,
  center = F,
  scale_unit = F,
  ncp = 100,
  ylim = c(0, 20),
  verbose = T,
  show_plot = NA,
  return_plot = NA,
  save_plot = NA,
  save_param = list(),
  default_save_name = "screePlot",
  ...
)

Arguments

gobject

giotto object

spat_unit

spatial unit

feat_type

feature type

name

name of PCA object if available

expression_values

expression values to use

reduction

cells or features

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

ylim

y-axis limits on scree plot

verbose

verobsity

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

...

additional arguments to pca function, see runPCA

Details

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').
Screeplot will use an available pca object, based on the parameter 'name', or it will create it if it's not available (see runPCA)

Value

ggplot object for scree method


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