iSEE package and functionality

Bioconductor conference 2019

Kevin Rue-Albrecht & Charlotte Soneson

Twitter: @KevinRUE67 & @csoneson

The team

Original wishlist (1 / 2)

  • An interactive user interface for exploring data in SummarizedExperiment objects
  • Particular focus given to single-cell data in the SingleCellExperiment derived class
  • Sample-oriented visualizations
  • Feature-oriented visualizations
  • Heat maps (cells and features)
  • Selectable points

Original wishlist (2 / 2)

  • Colouring of samples by metadata or assayed values
  • Stratify axes and facets by metadata (e.g., violin plots)
  • Hover and click
  • Zoom
  • Transmission of points selections between plots
  • Code tracking for reproducibility and batch generation of figures

iSEE(sce, voice=TRUE)

Creating an ExperimentColorMap

qc_color_fun <- function(n){
    qc_colors <- c("forestgreen", "firebrick1")
    names(qc_colors) <- c("Y", "N")
    qc_colors
}

ExperimentColorMap(
    assays = list(
        counts = heat.colors,
        logcounts = logcounts_color_fun,
        cufflinks_fpkm = fpkm_color_fun
    ),
    colData = list(
        passes_qc_checks_s = qc_color_fun
    ),
    all_continuous = list(
        assays = viridis::plasma
    ),
    global_continuous = viridis::viridis
)

Using an ExperimentColorMap object

colDataColorMap(ecm, "passes_qc_checks_s", discrete=TRUE)

How iSEE uses the ExperimentColorMap object

The iSEE-verse