Compare gene expression between polygon areas

Compare gene expression between polygon areas

comparePolygonExpression(
  gobject,
  polygon_name = "selections",
  spat_unit = "cell",
  feat_type = "rna",
  selected_feats = "top_genes",
  expression_values = "normalized",
  method = "scran",
  ...
)

Arguments

gobject

A Giotto object

polygon_name

name of polygon selections

spat_unit

spatial unit (e.g. "cell")

feat_type

feature type (e.g. "rna", "dna", "protein")

selected_feats

vector of selected features to plot

expression_values

gene expression values to use ("normalized", "scaled", "custom")

method

method to use to detect differentially expressed feats ("scran", "gini", "mast")

...

Arguments passed to Heatmap

Value

A ComplexHeatmap::Heatmap object

Examples

## Plot interactive polygons
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
#> 3.2 read Giotto spatial centroid information
#> 3.3 read Giotto spatial overlap information
#> 4. read Giotto image information
#> python already initialized in this session
#>  active environment : '/usr/bin/python3'
#>  python version : 3.10
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#>  "/usr/bin/python3"
my_polygon_coords <- data.frame(
    poly_ID = rep("polygon1", 3),
    sdimx = c(5477, 5959, 4720), sdimy = c(-4125, -2808, -5202)
)

## Add polygon coordinates to Giotto object
my_giotto_polygons <- createGiottoPolygonsFromDfr(my_polygon_coords,
    name = "selections"
)
#>   Selecting col "poly_ID" as poly_ID column
#>   Selecting cols "sdimx" and "sdimy" as x and y respectively
g <- addGiottoPolygons(
    gobject = g,
    gpolygons = list(my_giotto_polygons)
)

## Add polygon cells
g <- addPolygonCells(g)
#> 
#> These column names were already used: in_tissue nr_feats perc_feats total_expr
#>  leiden_clus custom_leiden
#>  and will be overwritten

comparePolygonExpression(g)
#> using 'Scran' to detect marker feats. If used in published
#>       research, please cite: Lun ATL, McCarthy DJ, Marioni JC (2016).
#>       'A step-by-step workflow for low-level analysis of single-cell RNA-seq
#>       data with Bioconductor.'
#>       F1000Res., 5, 2122. doi: 10.12688/f1000research.9501.2. 
#> start with cluster  no_polygonstart with cluster  polygon1