Instructor names and contact information
- Stefano Mangiola <mangiola.s at wehi.edu.au>
- Michael Love <michaelisaiahlove at gmail.com>
Conference Galaxy platform
You can find the workshop on the BioC2023 Galaxy platform listed as:
- Package Demo: tidySingleCellExperiment showing tidy genomic and transcriptomic analyses, for a single-cell RNA-seq application
Click here for a full list of the BioC2023 workshop demos.
Workshop package installation
If you want to install the packages and material post-workshop, the instructions are below. The workshop is designed for R 4.3 and Bioconductor 3.17.
#install.packages('remotes')
# Install workshop package
remotes::install_github("tidyomics/tidyomicsWorkshopBioc2023", build_vignettes = TRUE)
# To view vignette
library(tidyomicsWorkshopBioc2023)
vignette("tidyGenomicsTranscriptomics")To run the code, you could then copy and paste the code from the workshop vignette or R markdown file into a new R Markdown file on your computer.
Workshop Description
This tutorial will present how to perform analysis of single-cell RNA sequencing data following the tidy data paradigm. The tidy data paradigm provides a standard way to organise data values within a dataset, where each variable is a column, each observation is a row, and data is manipulated using an easy-to-understand vocabulary. Most importantly, the data structure remains consistent across manipulation and analysis functions.
This can be achieved with the integration of packages present in the R CRAN and Bioconductor ecosystem, including tidyseurat, tidySingleCellExperiment and tidyverse. These packages are part of the tidytranscriptomics suite that introduces a tidy approach to RNA sequencing data representation and analysis. For more information see the tidy transcriptomics blog.
In addition this workshop will finish with examples of how genomic and transcriptomic data can be combined, e.g. ChIP-seq and scRNA-seq, also using tidy data paradigms for genomic ranges. This is enabled with the plyranges package, with further information provided in the tidy-ranges-tutorial.
Pre-requisites
- Basic familiarity with single cell transcriptomic analyses
- Basic familiarity with tidyverse
- Basic familiarity with genomic ranges
Workshop Participation
The workshop format is a 45 minute session consisting of hands-on demos, exercises and Q&A.
Workshop goals and objectives
The tidytranscriptomics approach to single-cell RNA sequencing data analysis abstracts out the coding-related complexity and provides tools that use an intuitive and jargon-free vocabulary, enabling focus on the statistical and biological challenges.
Learning goals
- To approach data representation and analysis though a tidy data paradigm, integrating tidyverse with the SingleCellExperiment data object.
- To explore integration of genomic and transcriptomic data also using a tidy data paradigm.
What you will learn
- Basic
tidyoperations possible withtidySingleCellExperimentandGRanges - How to interface
SingleCellExperimentwith tidy manipulation and visualisation - A real-world case study that will showcase the power of
tidysingle-cell methods compared with base/ad-hoc methods - Examples of how to integrate genomic and transcriptomic data (ChIP-seq and RNA-seq)
