Summary and Schedule
This lesson provides an introduction to the Bioconductor project.
A good understanding of the Bioconductor project is the foundation to efficiently use Bioconductor packages for the analysis and visualization of -omics data using R and RStudio.
We download and install R packages from Bioconductor and other repositories to write workflows and perform analyses. In order to do so, we first identify packages that are available and relevant to our analysis, and we learn from their documentation the best practices to use them as their authors intended it. For reproducibility, it is also important to identify and track versions of packages used to perform each analysis.
Sometimes, we encounter bugs in packages that we use. While it is possible to report bugs to the authors and wait for issue to be fixed, packages hosted on public repositories offer the chance to inspect the code and contribute or propose fixes ourselves. In addition to being a great opportunity to develop coding skills, community contributors are very often recognized and credited for their contributions!
In this lesson, you will learn:
- To describe the Bioconductor project beyond software packages.
- To navigate the Bioconductor website to find packages for a particular task.
- To install and update Bioconductor packages.
- To open a package vignette and practice running through the examples that they contain.
- To identify standard classes and methods re-used across Bioconductor packages.
- To modify code and contribute to existing Bioconductor packages.
- Best practices to get help from packages developers and peers.
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Prerequisites
- Learning objectives of the Introduction to data analysis with R and Bioconductor workshop.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Introduction and setup |
Am I using the correct version of R for this lesson? Why does my version of R matter? How do I obtain the files that are used in this lesson? |
| Duration: 00h 10m | 2. Introduction to Bioconductor |
What does the Bioconductor project comprise? How does the Bioconductor project relate to the CRAN repository? How can I learn to use Bioconductor packages effectively? How do I join and communicate with the Bioconductor community? |
| Duration: 00h 20m | 3. Installing Bioconductor packages |
How do I install Bioconductor packages? How do I check if newer versions of my installed packages are available? How do I update Bioconductor packages? How do I find out the name of packages available from the Bioconductor repositories? |
| Duration: 00h 30m | 4. Getting help |
Where can I find help online? Where can I ask questions to package developers and other users? Where can I find documentation for a specific package? Where can I learn best practices to combine multiple package into a coherent workflow? |
| Duration: 00h 40m | 5. S4 classes in Bioconductor |
What is the S4 class system? How does Bioconductor use S4 classes? How is the Bioconductor DataFrame different
from the base data.frame?
|
| Duration: 00h 50m | 6. Working with biological sequences |
What is the recommended way to represent biological sequences in
Bioconductor? What Bioconductor packages provides methods to efficiently process biological sequences? |
| Duration: 01h 00m | 7. Working with genomics ranges |
What is the recommended way to represent coordinates on a genomic scale
in Bioconductor? What Bioconductor packages provides methods to efficiently process genomic ranges? How can I import/export sets of genomic coordinates from/to various genomic file formats? |
| Duration: 01h 10m | 8. Working with annotations |
What Bioconductor packages provides methods to efficiently fetch and use
gene annotations? How can I use gene annotation packages to convert between different gene identifiers? |
| Duration: 01h 20m | 9. The SummarizedExperiment class |
How is information organized in SummarizedExperiment objects? How can that information be added, edited, and accessed? |
| Duration: 01h 30m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
Ensure that you have the most recent versions of R and RStudio installed on your computer. For detailed instructions on how to do this, you can refer to the section “If you already have R and RStudio installed” in the Introduction to R episode of the Introduction to data analysis with R and Bioconductor lesson.
Additionally, you will also need to install the following packages that will be used throughout the lesson.
R
install.packages(c("BiocManager", "remotes"))
BiocManager::install(c(
"S4Vectors", "Biostrings", "BSgenome",
"BSgenome.Hsapiens.UCSC.hg38.masked",
"GenomicRanges", "rtracklayer", "biomaRt"))
If you are attending a workshop, please complete all of the above before the workshop. Should you need help, an instructor will be available 30 minutes before the workshop commences to assist.