Create visualization for cell proximity feature scores
plotCellProximityFeats(
gobject,
icfObject,
method = c("volcano", "cell_barplot", "cell-cell", "cell_sankey", "heatmap", "dotplot"),
min_cells = 4,
min_cells_expr = 1,
min_int_cells = 4,
min_int_cells_expr = 1,
min_fdr = 0.1,
min_spat_diff = 0.2,
min_log2_fc = 0.2,
min_zscore = 2,
zscores_column = c("cell_type", "feats"),
direction = c("both", "up", "down"),
cell_color_code = NULL,
show_plot = NULL,
return_plot = NULL,
save_plot = NULL,
save_param = list(),
default_save_name = "plotCellProximityFeats"
)Arguments
- gobject
giotto object
- icfObject
ICF (interaction changed feature) score object
- method
plotting method to use
- min_cells
minimum number of source cell type
- min_cells_expr
minimum expression level for source cell type
- min_int_cells
minimum number of interacting neighbor cell type
- min_int_cells_expr
minimum expression level for interacting neighbor cell type
- min_fdr
minimum adjusted p-value
- min_spat_diff
minimum absolute spatial expression difference
- min_log2_fc
minimum log2 fold-change
- min_zscore
minimum z-score change
- zscores_column
calculate z-scores over cell types or featuress
- direction
differential expression directions to keep
- cell_color_code
character. discrete colors to use. palette to use or named vector of colors
- show_plot
logical. show plot
- return_plot
logical. return ggplot object
- save_plot
logical. save the plot
- save_param
list of saving parameters, see
showSaveParameters- default_save_name
default save name for saving, don't change, change save_name in save_param
Value
volcano, cell_barplot, cell-cell, cell_sankey, heatmap, or dotplot
Examples
g <- GiottoData::loadGiottoMini("visium")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> cell_spatInfo_spatVector.shp
#> cell
#>
#> 3.2 read Giotto spatial centroid information
#> cell
#>
#> 3.3 read Giotto spatial overlap information
#> No overlaps were found, overlap loading will be
#> skipped
#>
#> 4. read Giotto image information
#> a giotto python environment was found
#> Using python path:
#> "/Users/yuanlab/Library/r-miniconda/envs/giotto_env/bin/pythonw"
icfObject <- findInteractionChangedFeats(g, cluster_column = "leiden_clus")
plotCellProximityFeats(gobject = g, icfObject = icfObject,
show_plot = TRUE, save_plot = FALSE, return_plot = FALSE)
