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The following is a full example of usage of the widget with a SingleCellExperiment object.

First, install the R dependencies:

install.packages("BiocManager")
BiocManager::install("scRNAseq")
BiocManager::install("scater")

Download the dataset, load and preprocess the SingleCellExperiment object, and configure the Vitessce widget:

library(vitessceR)
library(scRNAseq)
library(scater)

sce_zeisel <- ZeiselBrainData()

sce_zeisel <- addPerCellQC(sce_zeisel, subsets=list(Mito = grep("mt-", rownames(sce_zeisel))))
sce_zeisel <- logNormCounts(sce_zeisel) 
sce_zeisel <- runPCA(sce_zeisel)


# Create Vitessce view config
vc <- VitessceConfig$new("My config")
dataset <- vc$add_dataset("My dataset")$add_object(SCEWrapper$new(
  sce_zeisel,
  cell_set_metas = c("tissue", "level1class", "level2class"),
  cell_set_meta_names = c("Tissue", "Cell Type Level 1", "Cell Type Level 2"),
  cell_embeddings = c("PCA"),
  out_dir = file.path("data", "sce")
))
scatterplot <- vc$add_view(dataset, Component$SCATTERPLOT, mapping = "PCA")
status <- vc$add_view(dataset, Component$STATUS)
desc <- vc$add_view(dataset, Component$DESCRIPTION)
desc <- desc$set_props(description = "Visualization of a SingleCellExperiment object.")
cell_sets <- vc$add_view(dataset, Component$CELL_SETS)
heatmap <- vc$add_view(dataset, Component$HEATMAP)
vc$link_views(
  list(scatterplot, heatmap),
  list(CoordinationType$GENE_EXPRESSION_COLORMAP_RANGE),
  list(c(0.0, 0.05))
)
vc$layout(hconcat(
  vconcat(scatterplot, heatmap),
  vconcat(cell_sets, vconcat(desc, status))
))

# Render the Vitessce widget
vc$widget(theme = "light")