plot_clustering_consistency: Plot clustering consistency

In mariiabilous/SuperCellBM:

Description

Plot clustering consistency

Usage

plot_clustering_consistency(
  clust.consistency.df,
  consistency.index.name = "ARI",
  min.value.alt.clustering = 0,
  error_bars = c("extr", "quartiles", "sd")[1],
  fig.name = "",
  to.save.plot = TRUE,
  to.save.plot.raw = FALSE,
  asp = 0.5,
  fig.folder = "./plots",
  ignore.gammas = c(),
  ignore.methods = c(),
  .shapes = c(Exact = 1, Approx = 0, Subsampling = 2, Random = 3, Metacell_default_fp =
    4, Metacell_default_av = 8, Metacell_SC_like_fp = 4, Metacell_SC_like_av = 8,
    Alternative = 23),
  .colors = c(Exact = "darkred", Approx = "royalblue", Subsampling = "black", Random =
    "gray", Metacell_default_fp = "forestgreen", Metacell_default_av = "forestgreen",
    Metacell_SC_like_fp = "gold", Metacell_SC_like_av = "gold", Alternative = "darkblue"),
  verbose = FALSE,
  ...
)

Arguments

clust.consistency.df	output of compute_consistency_of_supercell_clustering
consistency.index.name	name of the consistency index (output of clustComp)
min.value.alt.clustering	min index value for the alternative clustering consistency
error_bars	name of values used for errorbars (for subsampling, random grouping, alternative clusteting of single cells and other methods with more than one clustering/simplification output). 'extr' for min/max, 'quartiles' for quartiles and 'sd' for meadin +- sd

mariiabilous/SuperCellBM documentation built on Jan. 28, 2022, 7:45 p.m.