Map cell markers to clusters (hypergeometric/jaccard) — plot_markers_to

Use jaccard index and hypergeometric to map a list of cell markers to gene clusters.

plot_markers_to_clusters(
  object,
  markers = NULL,
  gradient_palette = colors_for_gradient("Magma"),
  background = NULL,
  cell_type_order = c("None", "hclust"),
  only_specific = FALSE,
  jaccard_scale = 10
)

Arguments

object: A ClusterSet object.
markers: A list of cell markers.
gradient_palette: A vector of colors for the gradient palette.
background: The background for hypergeometric test. Typically the list of genes annotated in the considered gene ontology (e.g. BP).
cell_type_order: The order of cell types. Can be "None" or "hclust". Not supported at the moment.
only_specific: Logical value indicating whether to show only specific markers.
jaccard_scale: The scale factor for Jaccard coefficient.

Value

A plot showing the relationship between markers and clusters.

Examples

load_example_dataset("8028126/files/pbmc3k_medium_clusters_enr")
#> |-- INFO :  Dataset 8028126/files/pbmc3k_medium_clusters_enr was already loaded. 
library(clustermole)
m <- clustermole::clustermole_markers(species = "hs")
markers <- split(m$gene[m$organ == "Blood" & m$species == "Human"], 
                 m$celltype[m$organ == "Blood" & m$species == "Human"])
plot_markers_to_clusters(pbmc3k_medium_clusters_enr, markers=markers)
#> |-- INFO :  WARNING: Running without a background but you should probably provide one. 
#> |-- INFO :  Computing background from the union of set_1 and set_2. 
#> |-- INFO :  Computing background from the union of set_1 and set_2.