16 Interactive Data Exploration

Not every question is easiest to answer from a static figure or a scripted summary. Sometimes the fastest way to understand a dataset is to click, filter, inspect, and compare interactively.

sclet integrates iSEE to provide a Shiny-based interactive explorer for your SingleCellExperiment objects.

The examples in this chapter are shown but not executed during book rendering, because they launch an interactive Shiny session rather than producing a static result that can be embedded cleanly in the book. In other words, the issue here is not package availability but session lifetime: a documentation build should finish, whereas an interactive explorer is expected to stay open until the user closes it.

16.1 Launch Explorer

You can launch the explorer directly from your R console:

To reproduce this locally, the only real prerequisites are an SCE object with at least one usable assay and dimensional reduction, plus the iSEE package.

library(sclet)
sce <- readRDS("data/pbmc-3k-sce.rds")

# Launch the app
RunExplorer(sce)

This will open a web browser where you can:

  • Visualize reduced dimensions (UMAP, PCA)
  • Explore gene expression on the plot
  • Check column data (QC metrics, Clusters)
  • Select points and inspect data

16.2 Customization

RunExplorer passes additional arguments to iSEE::iSEE(), allowing you to pre-configure panels.

# Example: Start with just a ReducedDimensionPlot and a FeaturePlot
library(iSEE)
initial <- list(
    ReducedDimensionPlot(PanelId=1L),
    FeatureAssayPlot(PanelId=1L)
)

RunExplorer(sce, initial = initial)