README.md

iSEE - The interactive SummarizedExperiment Explorer

Software status

| Platforms | OS | R CMD check | Coverage | |:----------------:|:----------------:|:----------------:|:----------------:| | Travis CI | Linux | Travis CI build status | Codecov.io coverage status | | Bioc (devel) | Multiple | Bioconductor-devel Build Status | NA | | Bioc (release) | Multiple | Bioconductor-release Build Status | NA |

Overview

The iSEE package provides an interactive user interface for exploring data in objects derived from the SummarizedExperiment class. Particular focus is given to single-cell data stored in the SingleCellExperiment derived class. The user interface is implemented with RStudio's Shiny, with a multi-panel setup for ease of navigation.

This initiative was proposed at the European Bioconductor Meeting in Cambridge, 2017. Current contributors include:

Figure 1. _iSEE_ uses a customisable multi-panel layout.

Functionalities

The user interface of iSEE web-applications currently offers the following features:

:white_check_mark: Multiple interactive plot types with selectable points.

:white_check_mark: Interactive tables with selectable rows.

:white_check_mark: Coloring of samples and features by metadata or expression data.

:white_check_mark: Zooming to a plot subregion.

:white_check_mark: Transmission of point selections between panels to highlight, color, or restrict data points in the receiving panel(s).

:white_check_mark: Lasso point selection to define complex shapes.

Sample-level visualization

The iSEE user interface currently contains the following components where each data point represents a single biological sample:

:white_check_mark: Reduced dimension plot: Scatter plot of reduced dimensionality data.

:white_check_mark: Column data plot: Adaptive plot of any one or two sample metadata. A scatter, violin, or square design is dynamically applied according to the continuous or discrete nature of the metadata.

:white_check_mark: Feature assay plot: Adaptive plot of expression data across samples for any two features or one feature against one sample metadata.

:white_check_mark: Column statistics table: Table of sample metadata.

Feature-level visualization

The iSEE user interface currently contains the following components where each data point represents a genomic feature:

:white_check_mark: Row data plot: Adaptive plot of any two feature metadata. A scatter, violin, or square design is dynamically applied according to the continuous or discrete nature of the metadata.

:white_check_mark: Sample assay plot: Adaptive plot of expression data across features for any two samples or one sample against one feature metadata.

:white_check_mark: Row statistics table: Table of feature metadata.

Integrated visualization

The iSEE user interface contains the following components that integrate sample and feature information:

:white_check_mark: Heat map plot: Visualize multiple features across multiple samples annotated with sample metadata.

Custom panels

The iSEE user interface allows users to programmatically define their own plotting and table panels.

:white_check_mark: Custom data plot: Plotting panel that can be assigned any user-defined function returning a ggplot object.

:white_check_mark: Custom statistics table: Table panel that can be assigned any user-defined function returning a data.frame object.

Miscellaneous

:white_check_mark: The iSEE user interface continually tracks the code corresponding to all visible plotting panels. This code is rendered in a shinyAce text editor and can be copy-pasted into R scripts for customization and further use.

Want to try iSEE?

We set up instances of iSEE applications running on diverse types of datasets at those addresses:

Please keep in mind that those public instances are for trial purposes only; yet they demonstrate how you or your system administrator can setup iSEE for analyzing or sharing your precomputed SummarizedExperiment/SingleCellExperiment object.



csoneson/iSEE documentation built on Oct. 19, 2018, 7:25 p.m.