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Plot the results of the search for good parameters

plot_find_best_params_results.Rd

Plot the results of the search for good parameters

Usage

plot_find_best_params_results(
  find_best_params_results,
  bin_count_colors = viridis::scale_color_viridis(option = "viridis"),
  gene_count_colors = viridis::scale_color_viridis(option = "magma")
)

Arguments

find_best_params_results

Results dataframe from find_best_params()

bin_count_colors

Optional, custom bin count color scheme.

gene_count_colors

Optional, custom gene count color scheme.

Value

A plot showing how convexity changes as n_bins and n_genes are changed. See find_best_params() for details on how to interpret.

See also

find_best_params()

Examples

ncells <- 70
ngenes <- 100
counts_matrix <- matrix(
    c(seq_len(3500) / 10, seq_len(3500) / 5),
    ncol = ncells,
    nrow = ngenes
)
sce <- SingleCellExperiment::SingleCellExperiment(assays = list(
    normcounts = counts_matrix, logcounts = log(counts_matrix)
))
colnames(sce) <- paste0("cell", seq_len(ncells))
rownames(sce) <- paste0("gene", seq_len(ngenes))
sce$cell_type <- c(
    rep("celltype_1", ncells / 2),
    rep("celltype_2", ncells / 2)
)

sce$pseudotime <- seq_len(ncells) - 1
genelist <- rownames(sce)

# Finding the best params for the BlaseData
best_params <- find_best_params(
    sce, genelist,
    bins_count_range = c(2, 3),
    gene_count_range = c(20, 50),
    pseudotime_slot = "pseudotime",
    split_by = "pseudotime_range"
)
best_params
#>   column_label bin_count gene_count min_convexity mean_convexity
#> 1            1         2         20             0              0
#> 2            2         2         50             0              0
#> 3            1         3         20             0              0
#> 4            2         3         50             0              0
#>   confident_mapping_pct
#> 1                     0
#> 2                     0
#> 3                     0
#> 4                     0
plot_find_best_params_results(best_params)