doGiottoClustree

Source: R/clustering.R

cluster cells using leiden methodology to visualize different resolutions

doGiottoClustree(
  gobject,
  res_vector = NULL,
  res_seq = NULL,
  return_gobject = FALSE,
  show_plot = NULL,
  save_plot = NULL,
  return_plot = NULL,
  save_param = list(),
  default_save_name = "clustree",
  verbose = TRUE,
  ...
)

Arguments

gobject

giotto object

res_vector

vector of different resolutions to test

res_seq

list of float numbers indicating start, end, and step size for resolution testing, i.e. (0.1, 0.6, 0.1)

return_gobject

default FALSE. See details for more info.

show_plot

by default, pulls from provided gobject instructions

save_plot

by default, pulls from provided gobject instructions

return_plot

by default, pulls from provided gobject instructions

save_param

list of saving parameters from GiottoVisuals::all_plots_save_function()

default_save_name

name of saved plot, default "clustree"

verbose

be verbose

...

Arguments passed on to clustree::clustree

Value

a plot object (default), OR a giotto object (if specified)

Details

This function tests different resolutions for Leiden clustering and provides a visualization of cluster sizing as resolution varies.

By default, the tested leiden clusters are NOT saved to the Giotto object, and a plot is returned.

If return_gobject is set to TRUE, and a giotto object with all tested leiden cluster information will be returned.

See also

doLeidenCluster

Examples

g <- GiottoData::loadGiottoMini("visium")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> 3.2 read Giotto spatial centroid information
#> 3.3 read Giotto spatial overlap information
#> 4. read Giotto image information
#> 
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#>  "/usr/bin/python3"

doGiottoClustree(
    gobject = g, res_vector = c(0.5, 0.8), return_plot = FALSE,
    show_plot = FALSE, save_plot = FALSE
)
#> Error: package 'clustree' is not yet installed
#> 
#>  To install:
#> install.packages(c("clustree"))