iSEE {iSEE} | R Documentation |
Interactive and reproducible visualization of data contained in a SummarizedExperiment/SingleCellExperiment, using a Shiny interface.
iSEE(se, redDimArgs = NULL, colDataArgs = NULL, featAssayArgs = NULL, rowStatArgs = NULL, rowDataArgs = NULL, sampAssayArgs = NULL, colStatArgs = NULL, customDataArgs = NULL, customStatArgs = NULL, heatMapArgs = NULL, redDimMax = 5, colDataMax = 5, featAssayMax = 5, rowStatMax = 5, rowDataMax = 5, sampAssayMax = 5, colStatMax = 5, customDataMax = 5, customStatMax = 5, heatMapMax = 5, initialPanels = NULL, annotFun = NULL, customDataFun = NULL, customStatFun = NULL, colormap = ExperimentColorMap(), tour = NULL, appTitle = NULL, runLocal = TRUE)
se |
An object that is coercible to SingleCellExperiment. |
redDimArgs |
A DataFrame similar to that produced by |
colDataArgs |
A DataFrame similar to that produced by |
featAssayArgs |
A DataFrame similar to that produced by |
rowStatArgs |
A DataFrame similar to that produced by |
rowDataArgs |
A DataFrame similar to that produced by |
sampAssayArgs |
A DataFrame similar to that produced by |
colStatArgs |
A DataFrame similar to that produced by |
customDataArgs |
A DataFrame similar to that produced by |
customStatArgs |
A DataFrame similar to that produced by |
heatMapArgs |
A DataFrame similar to that produced by |
redDimMax |
An integer scalar specifying the maximum number of reduced dimension plots in the interface. |
colDataMax |
An integer scalar specifying the maximum number of column data plots in the interface. |
featAssayMax |
An integer scalar specifying the maximum number of feature assay plots in the interface. |
rowStatMax |
An integer scalar specifying the maximum number of row statistics tables in the interface. |
rowDataMax |
An integer scalar specifying the maximum number of row data plots in the interface. |
sampAssayMax |
An integer scalar specifying the maximum number of sample assay plots in the interface. |
colStatMax |
An integer scalar specifying the maximum number of column statistics tables in the interface. |
customDataMax |
An integer scalar specifying the maximum number of custom data plots in the interface. |
customStatMax |
An integer scalar specifying the maximum number of custom statistics tables in the interface. |
heatMapMax |
An integer scalar specifying the maximum number of heatmaps in the interface. |
initialPanels |
A DataFrame specifying which panels should be created at initialization.
This should contain a |
annotFun |
A function, similar to those returned by |
customDataFun |
A named list of functions for reporting coordinates to use in a custom data plot. |
customStatFun |
A named list of functions for reporting coordinates to use in a custom statistics table. |
colormap |
An ExperimentColorMap object that defines custom colormaps to apply to individual |
tour |
A data.frame with the content of the interactive tour to be displayed after starting up the app. |
appTitle |
A string indicating the title to be displayed in the app.
If not provided, the app displays the version info of |
runLocal |
A logical indicating whether the app is to be run locally or remotely on a server, which determines how documentation will be accessed. |
Users can pass default parameters via DataFrame objects in redDimArgs
and featAssayArgs
.
Each object can contain some or all of the expected fields (see redDimPlotDefaults
).
Any missing fields will be filled in with the defaults.
The number of maximum plots for each type of plot is set to the larger of *Max
and nrow(*Args)
.
Users can specify any number of maximum plots, though increasing the number will increase the time required to render the interface.
The initialPanels
argument specifies the panels to be created upon initializing the interface.
This should be a DataFrame containing a Name
field specifying the identity of the panel, e.g., "Reduced dimension plot 1"
, "Row statistics table 2"
.
Please refer to availablePanelTypes
for the full list of panels available.
The trailing number should not be greater than the number of maximum plots of that type.
Users can also define the Width
field, specifying the width of each panel from 2 to 12 (values will be coerced inside this range);
and the Height
field, specifying the height of each panel from 400 to 1000 pixels.
By default, one panel of each type (where possible) will be generated, with height of 500 and width of 4.
The tour
argument needs to be provided in a form compatible with the format expected by the rintrojs
package.
There should be two columns, element
and intro
, with the former describing the element to highlight and the latter providing some descriptive text.
See https://github.com/carlganz/rintrojs#usage for more information.
By default, categorical data types such as factor and character are limited to 24 levels, beyond which they are coerced to numeric variables for faster plotting.
This limit may be set to a different value as a global option, e.g. options(iSEE.maxlevels=30)
.
A Shiny app object is returned, for interactive data exploration of the SummarizedExperiment or SingleCellExperiment object.
library(scRNAseq) data(allen) class(allen) # Example data ---- library(scater) sce <- as(allen, "SingleCellExperiment") counts(sce) <- assay(sce, "tophat_counts") sce <- normalize(sce) sce <- runPCA(sce, ncomponents=4) sce <- runTSNE(sce) rowData(sce)$ave_count <- rowMeans(counts(sce)) rowData(sce)$n_cells <- rowSums(counts(sce)>0) sce # launch the app itself ---- app <- iSEE(sce) if (interactive()) { shiny::runApp(app, port = 1234) }