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iSEE: Interactive visualization of SummarizedExperiment objects

Instructor(s) name(s) and contact information

Key resources

Workshop Description

This workshop demonstrates the use of the iSEE package to create and configure interactive applications for the exploration of various types of genomics data sets (e.g., bulk and single-cell RNA-seq, CyTOF, gene expression microarray).

This workshop will be presented as a lab session that combines an instructor-led live demo, followed by hands-on experimentation guided by exercises, hints, and comprehensive solutions that participants may continue to use after the workshop.

The instructor-led live demo comprises three parts:

  1. Overview of the preprocessed data set used for this workshop.
  2. Brief demonstration of graphical user interface and package functionality.
  3. Hands-on exercises and discussion.

Participants are encouraged to ask questions at any time during the workshop.

Pre-requisites

Additional background reading about the programming environment, relevant packages, and example use cases:

Workshop Participation

Students will participate by following along an R markdown document, and asking questions throughout the workshop. There is also scope for participants to apply iSEE to their own data sets, and fuel the discussion with more questions about specific use cases.

R / Bioconductor packages used

  1. iSEE : https://bioconductor.org/packages/iSEE
  2. SummarizedExperiment: https://bioconductor.org/packages/SummarizedExperiment
  3. SingleCellExperiment: https://bioconductor.org/packages/SingleCellExperiment
  4. scater: https://bioconductor.org/packages/scater
  5. scran: https://bioconductor.org/packages/scran
  6. TENxPBMCData: https://bioconductor.org/packages/TENxPBMCData
  7. BiocSingular: https://bioconductor.org/packages/BiocSingular

Time outline

Activity Time
Overview of the example data set. 15m
Demonstration of the package functionality 15m
Hands on exercises 90m

Total: 2h

Workshop goals and objectives

Learning goals

  • Recognize the benefits of integrative data containers such as SummarizedExperiment and SingleCellExperiment for downstream analyses and visualization
  • Outline the unique features of iSEE built upon the RStudio Shiny framework
  • Identify biological data that may be combined into insightful graphical outputs
  • Utilize interactive GUI components and layouts to efficiently extract information from biological data sets
  • Describe how to construct interactive apps and custom panels

Learning objectives

  • Memorize the key information available in SummarizedExperiment and SingleCellExperiment objects
  • Set up a local environment for running iSEE apps
  • Interact with components of the iSEE user interface to visually inspect and discuss various data sets
  • Identify and locate configurable aspects of iSEE apps
  • Practice interactive visualization over a single-cell RNA-sequencing workflow
  • Design custom iSEE panels for advanced use cases
  • Imagine use cases and future developments for interactive visualization as part of computational workflows

Docker setup

In the Docker settings menu:

  • Open ‘Preferences…’
  • Navigate to ‘Resources’
  • Use the slider to set ‘Memory’ to ‘4.00 GB’
  • Click ‘Apply & Restart’

Workshop setup

  • Run docker pull iseedevelopers/iseeworkshopeurobioc2020
  • Run docker run -e PASSWORD=isee -p 8787:8787 -d --rm iseedevelopers/iseeworkshopeurobioc2020. Use -v $(pwd):/home/rstudio argument to map your local directory to the container.
  • Log in to RStudio at http://localhost:8787 using username rstudio and password isee. Note that on Windows you need to provide your localhost IP address like http://191.163.92.108:8787/ - find it using docker-machine ip default in Docker’s terminal.
  • Run browseVignettes(package = "iSEEWorkshopEuroBioc2020"). Click on one of the links, “HTML”, “source”, “R code”.