This vignette provides an overview of the graphical interface of iSEE applications. To follow along, make sure that you launch the default iSEE instance as described in the start of the next section.
Note that in the default configuration, the panels do not look exactly like the ones shown in the screenshots that you will see below. For example, data points are not immediately colored, and the default annotation variables displayed by each panel may differ.
Also note that for simplicity, we typically refer to a
SummarizedExperiment in this workshop; however, iSEE works
seamlessly for objects of any class extending
SummarizedExperiment as well (e.g.,
SingleCellExperiment, DESeqDataSet). That
said, some types of panels – such as the Reduced dimension plot – are
only available for objects that contain a reducedDim slot
(in particular, SingleCellExperiment objects); the basic
SummarizedExperiment class does not contain this slot. In
this workshop, we refer to the rows of the
SummarizedExperiment object as ‘features’ (these can be
genes, transcripts, proteins, genomic regions, etc) and to the columns
as ‘samples’ (which, in our example data set, are single cells).
Using the demonstration data set, we can launch an iSEE
instance for exploring this data set using the iSEE()
function without any arguments beyond the data set. This will produce an
app using the default configuration; that is, the app instance will
include one panel of each built-in class for which the required
information is available in the SummarizedExperiment
object.
You can download the example data set from Dropbox.
library(iSEE)
sce <- readRDS("sce-tenxpbmcdata-pbmc3k-isee.rds")
app <- iSEE(sce)shiny::runApp(app)