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Pharmacogenomics CBW 2024

The Canadian Bioinformatics Workshops (CBW) are a series of hands-on training sessions that provide bioinformatics training to biologists, researchers, and other professionals.

Each workshop is designed to provide both theoretical knowledge and practical experience, ensuring participants leave with the skills and tools to apply bioinformatics techniques to their own research.

Overview: Pharmacogenomics Data Analysis

This workshop delves into the rapidly advancing field of personalized cancer treatment, emphasizing how treatments can be tailored to individual patients based on their unique molecular profiles. Participants will gain a foundational understanding of pharmacogenomics, focusing specifically on cancer biomarker analysis, and will be guided through a comprehensive workflow from basic concepts to advanced biomarker discovery techniques. Participants will be introduced to the PharmacoGx package and how to use it to analyze pharmacogenomics data. Through hands-on tutorials and practical exercises, participants will learn how to extract, analyze, and visualize data to identify robust cancer biomarkers, with transferable skills applicable to other areas of disease research.

Note: This workshop is accompanied by 4 presentations.

Distribution: The workshop is developed as an R package. The package contains vignettes, and data that correspond to the workshop modules.

The workshop will also be published by the CBW Workshop Website

By visiting the published workshop, you can see the following modules:

  1. Module 1 Lab: Getting to know multi-omics data (Julia, Nikta, Jermiah)
  2. Module 2 Lab: Hands-on with pharmacogenomics data (Jermiah, Almas)
  3. Module 3: Pharmacogenomics for biomarker discovery - Basic analysis (Nikta, Julia)
  4. Module 4: Pharmacogenomics for biomarker discovery - Advanced analysis (Nikta, Julia)

To view the vignettes, click on the articles tab in the package landing page.

Setup for Workshop Participants

Installing from GitHub

Run to install this package and its dependencies.

pak::pkg_install("bhklab/CBWWorkshop2024", dependencies=TRUE)

[!NOTE]
You may need to install the pak package first. pak is a “Fresh Approach to R Package Installation”. You can install it by running:

Contributing

Adding to the repo

  1. Installing developer tools

If you haven’t worked with R packages before, some packages make life a lot easier. You can install them by running the following command in R:

pkgs <- c("devtools", "usethis", "roxygen2", "testthat", "biocthis")
pak::pkg_install(pkgs)
  1. Clone the repository and create a new branch
git clone https://github.com/bhklab/CBWWorkshop2024.git
cd CBWWorkshop2024
git checkout -b <your-branch-name>
  1. Add your changes

Example 1: add yourself as an author to the package

usethis::use_author("firstname", "secondname", role="aut")
# your name should now appear in the description file

Example 2: Add a new vignette

# Make a new Vignette
biocthis::use_bioc_vignette("Module3", "Module 3: TITLE")

# Your vignette should be in the vignettes folder
# Make a bunch of changes, atleast delete all the auto-generated
# and add your own content
  1. Commit and push your changes
git add .
git commit -m "DESCRIPTIVE MESSAGE"
git push
  1. Create a pull request

Visit the github repo and create a pull request at https://github.com/bhklab/CBWWorkshop2024

Merging changes from the main branch

If the main branch has been updated, you can merge the changes into your branch by running the following commands:

git fetch origin
git checkout main
git pull

Then, merge the changes into your branch

git checkout <your-branch-name>
git merge origin/main

If there are conflicts, you will need to resolve them before you can merge the changes. See this helpful guide on resolving conflicts: