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README.md
<img src="inst/www/iSEE.png" align="right" alt="" width="120" /> # _iSEE_ - The interactive SummarizedExperiment Explorer <!-- badges: start --> [![GitHub issues](https://img.shields.io/github/issues/iSEE/iSEE)](https://github.com/iSEE/iSEE/issues) [![GitHub pulls](https://img.shields.io/github/issues-pr/iSEE/iSEE)](https://github.com/iSEE/iSEE/pulls) [![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-green.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable) [![R-CMD-check-bioc](https://github.com/iSEE/iSEE/workflows/R-CMD-check-bioc/badge.svg)](https://github.com/iSEE/iSEE/actions) [![Codecov test coverage](https://codecov.io/gh/iSEE/iSEE/branch/main/graph/badge.svg)](https://app.codecov.io/gh/iSEE/iSEE?branch=main) <!-- badges: end --> ## Bioconductor release status | Branch | R CMD check | Last updated | |:----------------:|:----------------:|:------------:| | [_devel_](http://bioconductor.org/packages/devel/bioc/html/iSEE.html) | [![Bioconductor-devel Build Status](http://bioconductor.org/shields/build/devel/bioc/iSEE.svg)](http://bioconductor.org/checkResults/devel/bioc-LATEST/iSEE) | ![](http://bioconductor.org/shields/lastcommit/devel/bioc/iSEE.svg) | | [_release_](http://bioconductor.org/packages/release/bioc/html/iSEE.html) | [![Bioconductor-release Build Status](http://bioconductor.org/shields/build/release/bioc/iSEE.svg)](http://bioconductor.org/checkResults/release/bioc-LATEST/iSEE) | ![](http://bioconductor.org/shields/lastcommit/release/bioc/iSEE.svg) | ## 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](https://www.rstudio.com)'s [_Shiny_](https://shiny.rstudio.com), with a multi-panel setup for ease of navigation. This initiative was proposed at the European Bioconductor Meeting in Cambridge, 2017. Current contributors include: - [Charlotte Soneson](https://github.com/csoneson) - [Aaron Lun](https://github.com/LTLA) - [Federico Marini](https://github.com/federicomarini) - [Kévin Rue-Albrecht](https://github.com/kevinrue) [![Figure 1. _iSEE_ uses a customisable multi-panel layout.][Figure1]](https://f1000research.com/articles/7-741/v1) ## Installation _iSEE_ can be easily installed from Bioconductor using `BiocManager::install()`: ```r if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("iSEE") # or also... BiocManager::install("iSEE", dependencies = TRUE) ``` Setting `dependencies = TRUE` should ensure that all packages, including the ones in the `Suggests:` field of the `DESCRIPTION`, are installed - this can be essential if you want to reproduce the code in the vignette, for example. ## Functionalities <details> <summary><b> Click to expand the list of features available in <i>iSEE</i> applications. </b></summary> ### General * Multiple interactive plot types with selectable points. * Interactive tables with selectable rows. * Coloring of samples and features by metadata or expression data. * Zooming to a plot subregion. * Transmission of point selections between panels to highlight, color, or restrict data points in the receiving panel(s). * 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: * **Reduced dimension plot**: Scatter plot of reduced dimensionality data. * **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. * **Feature assay plot**: Adaptive plot of expression data across samples for any two features or one feature against one sample metadata. * **Column data 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: * **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. * **Sample assay plot**: Adaptive plot of expression data across features for any two samples or one sample against one feature metadata. * **Row data table**: Table of feature metadata. ### Integrated visualization The _iSEE_ user interface contains the following components that integrate sample and feature information: * **Complex heatmap plot**: Visualize multiple features across multiple samples annotated with sample metadata. ### Custom panels The _iSEE_ API allows users to programmatically define their own plotting and table panels. See the section [Extending _iSEE_](#extending-isee) further below. ### Miscellaneous * The _iSEE_ user interface continually tracks the code corresponding to all visible plotting panels. This code is rendered in a [shinyAce](https://cran.r-project.org/web/packages/shinyAce/index.html) text editor and can be copy-pasted into R scripts for customization and further use. * Speech recognition can be enabled to control the user interface using voice commands. </details> ## Want to try _iSEE_? We set up instances of _iSEE_ applications running on diverse types of datasets at those addresses: - http://shiny.imbei.uni-mainz.de:3838/iSEE - https://marionilab.cruk.cam.ac.uk/iSEE_allen - https://marionilab.cruk.cam.ac.uk/iSEE_tcga - https://marionilab.cruk.cam.ac.uk/iSEE_pbmc4k - https://marionilab.cruk.cam.ac.uk/iSEE_cytof 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. ## Extending _iSEE_ If you want to extend the functionality of _iSEE_, you can create custom panels which add new possibilities to interact with your data. Custom panels can be defined in independent R packages that include _iSEE_ in the `Imports:` sections of their DESCRIPTION file. You can find a collection of working examples of how to do it in [iSEEu](https://github.com/iSEE/iSEEu). Feel free to contact the developing team, should you need some clarifications on how _iSEE_ works internally. [Figure1]: https://f1000researchdata.s3.amazonaws.com/manuscripts/16293/6bf85f9d-8352-4a78-a8da-456f05f5c4c9_figure1.gif "iSEE uses a customisable multi-panel layout" ## Code of Conduct Please note that the iSEE project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.