filterCombinations

Shows how many genes and cells are lost with combinations of thresholds.

filterCombinations(
  gobject,
  expression_values = c("raw", "normalized", "scaled", "custom"),
  expression_thresholds = c(1, 2),
  gene_det_in_min_cells = c(5, 50),
  min_det_genes_per_cell = c(200, 400),
  scale_x_axis = "identity",
  x_axis_offset = 0,
  scale_y_axis = "identity",
  y_axis_offset = 0,
  show_plot = TRUE,
  return_plot = FALSE,
  save_plot = NA,
  save_param = list(),
  default_save_name = "filterCombinations"
)

Arguments

gobject	giotto object
expression_values	expression values to use
expression_thresholds	all thresholds to consider a gene expressed
gene_det_in_min_cells	minimum number of cells that should express a gene to consider that gene further
min_det_genes_per_cell	minimum number of expressed genes per cell to consider that cell further
scale_x_axis	ggplot transformation for x-axis (e.g. log2)
x_axis_offset	x-axis offset to be used together with the scaling transformation
scale_y_axis	ggplot transformation for y-axis (e.g. log2)
y_axis_offset	y-axis offset to be used together with the scaling transformation
show_plot	show plot
return_plot	return only 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

Value

list of data.table and ggplot object

Details

Creates a scatterplot that visualizes the number of genes and cells that are lost with a specific combination of a gene and cell threshold given an arbitrary cutoff to call a gene expressed. This function can be used to make an informed decision at the filtering step with filterGiotto.

Examples

data(mini_giotto_single_cell)

# assess the effect of multiple filter criteria
filterCombinations(mini_giotto_single_cell,
gene_det_in_min_cells = c(2, 4, 8),
min_det_genes_per_cell = c(5, 10, 20))
#> Loading required package: Matrix
#> $results
#>    threshold gene_detected_in_min_cells min_detected_genes_per_cell combination
#> 1:         1                          2                           5         2-5
#> 2:         1                          4                          10        4-10
#> 3:         1                          8                          20        8-20
#> 4:         2                          2                           5         2-5
#> 5:         2                          4                          10        4-10
#> 6:         2                          8                          20        8-20
#>    removed_genes removed_cells
#> 1:             0             0
#> 2:             0             7
#> 3:             4            20
#> 4:             0             0
#> 5:             4            16
#> 6:             8            20
#> 
#> $ggplot
#>