filterCombinations#
Last Updated: Sep 07, 2023
Description#
Shows how many genes and cells are lost with combinations of thresholds.
Usage#
filterCombinations(
gobject,
feat_type = NULL,
spat_unit = NULL,
expression_values = c("raw", "normalized", "scaled", "custom"),
expression_thresholds = c(1, 2),
feat_det_in_min_cells = c(5, 50),
gene_det_in_min_cells = NULL,
min_det_feats_per_cell = c(200, 400),
min_det_genes_per_cell = NULL,
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#
|
giotto object |
|
feature type |
|
spatial unit |
|
expression values to use |
|
all thresholds to consider a gene expressed |
|
minimum # of cells that need to express a feature |
|
deprecated, use feat_det_in_min_cells |
|
minimum # of features that need to be detected in a cell |
|
deprecated, use min_det_feats_per_cell |
|
ggplot transformation for x-axis (e.g. log2) |
|
x-axis offset to be used together with the scaling transformation |
|
ggplot transformation for y-axis (e.g. log2) |
|
y-axis offset to be used together with the scaling transformation |
|
show plot |
|
return only ggplot object |
|
directly save the plot [boolean] |
|
list of saving parameters from
|
|
default save name for saving, don’t change, change save_name in save_param |
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.
Value#
list of data.table and ggplot object