README.md

iSEE - 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 aims to provide an interactive user interface for exploring data in objects derived from the SummarizedExperiment class. Particular focus will be given to single-cell data in the SingleCellExperiment derived class. The 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.

Cell-based visualizations

The interface is proposed to contain the following features in its first iteration:

:white_check_mark: multiple interactive scatter plots with selectable points

:white_check_mark: colouring of samples by metadata or expression values

:white_check_mark: zooming in to a particular subregion of the plot, if requested

:white_check_mark: scatter plots can be generated from reduced dimensionality data, or with biaxial plots of existing metadata columns.

Gene-based visualization

The interface is proposed to contain the following features in its first iteration:

:white_check_mark: boxplots of expression values for a single gene, stratified by metadata level

:white_check_mark: heatmaps of multiple genes for groups of cells or for individual ordered cells

:white_check_mark: integrated brushing in cell-based scatter plots with cell identities in gene-level plots

Miscellaneous

:white_check_mark: The interface will contain a continually updated R interface that provides the R code corresponding to each user interaction. This can be copy-pasted into R scripts for batch generation of figures.

Want to try iSEE?

We set up an instance of iSEE running on the allen dataset at this address: http://shiny.imbei.uni-mainz.de:3838/iSEE. Please keep in mind this is only for trial purposes, yet it can show a quick way of how you or your system administrator can setup r Biocpkg("iSEE") for analyzing your SummarizedExperiment/SingleCellExperiment precomputed object.



csoneson/iSEE documentation built on Aug. 14, 2018, 2:20 a.m.