Interactive Visualization of SummarizedExperiment Objects with iSEE (original) (raw)

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 completely worked examples and stand-alone notes that participants may continue to use after the workshop.

The instructor-led live demo comprises three parts:

1. Brief lecture on the package concept and functionality
2. Overview of the graphical user interface
3. Instructions to preconfigure iSEE apps

The hands-on lab comprises three part:

1. Inspection of single-cell RNA-seq data at various steps of a typical computational workflow, including quality control and dimensionality reduction
2. Addition of custom panels to the user interface for advanced visualization.
3. Additional questions from the participants, including individual use cases and suggestions for future developments

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

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

Time outline

Total: 1h45

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