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))