Instructor names and contact information
- Maria Doyle <Maria.Doyle at petermac.org>
- Stefano Mangiola <mangiola.s at wehi.edu.au>
Workshop package installation
This is necessary in order to reproduce the code shown in the workshop. The workshop is designed for R 4.1 and can be installed using one of the two ways below.
Via Docker image
If you’re familiar with Docker you could use the Docker image which has all the software pre-configured to the correct versions.
docker run -e PASSWORD=abc -p 8787:8787 stemangiola/bioc2021_tidytranscriptomics:bioc2021Once running, navigate to http://localhost:8787/ and then login with Username:rstudio and Password:abc.
You should see the Rmarkdown file with all the workshop code which you can run.
Via GitHub
Alternatively, you could install the workshop using the commands below in R 4.1.
#install.packages('remotes')
# Need to set this to prevent installation erroring due to even tiny warnings, similar to here: https://github.com/r-lib/remotes/issues/403#issuecomment-748181946
Sys.setenv("R_REMOTES_NO_ERRORS_FROM_WARNINGS" = "true")
# Install same versions used in the workshop
remotes::install_github(c("stemangiola/tidybulk@v1.4.0"", "stemangiola/tidySummarizedExperiment@v1.2.0", "stemangiola/tidySingleCellExperiment@v1.3.0"))
# Install workshop package
remotes::install_github("stemangiola/bioc2021_tidytranscriptomics", build_vignettes = TRUE)
# To view vignettes
library(bioc2021tidytranscriptomics)
browseVignettes("bioc2021tidytranscriptomics")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
Recently, plyranges and tidybulk have made efforts toward the harmonization of biological data structures and workflows using the concept of data tidiness, to facilitate modularisation. In this workshop, we present tidySingleCellExperiment and tidySummarizedExperiment, two R packages that allow the user to visualise and manipulate SingleCellExperiment and SummarizedExperiment objects in a tidy fashion. Importantly, the tidybulk framework now works natively with SummarizedExperiment objects and, thanks to tidySummarizedExperiment, allows tidy and modular RNA sequencing analyses without renouncing the efficiency of Bioconductor data containers. These tools are part of the tidytranscriptomics R software suite, and represent an effort toward the harmonisation of transcriptional analyses under the tidy umbrella.
Pre-requisites
- Some familiarity with tidyverse syntax
- Some familiarity with bulk RNA-seq and single cell RNA-seq
Recommended Background Reading Introduction to R for Biologists
Workshop Participation
The workshop format is a 1.5 hour session consisting of hands-on demos, challenges and Q&A.
R / Bioconductor packages used
- tidySummarizedExperiment
- tidySingleCellExperiment
- tidybulk
- tidyHeatmap
- limma
- edgeR
- DESeq2
- airway
- org.Hs.eg.db
- dittoSeq
- ggrepel
- GGally
- plotly
Time outline
Guide
| Activity - Hands on demos with Q&A | Time |
|---|---|
| Part 1 Bulk RNA-seq with tidySummarizedExperiment and tidybulk | 45 |
| Part 2 Single-cell RNA-seq with tidySingleCellExperiment | 45 |
| Total | 90m |
