Check out the introduction slides to review the goals and context for the event! If you’re interested in learning more, links to relevant papers are included in the Useful Links section below. There are a couple ways that you can get started.
- If you have R already installed and ready to go, clone or download this repository to your computer and open the
.Rmd files with RStudio or any other editor that you’re comfortable using.
- If you don’t have R installed on your computer, create a free account with RStudio Cloud, click the blue dropdown arrow next to [New Project], select [New Project from Git Repo], and enter this GitHub repo URL: https://github.com/pkimes/PR2020replicathon
Free accounts on RStudio Cloud have unlimited access to cloud computing until August 3, 2020! Unfortunately, after that, free accounts will be limited to 15 hours per month.
After going over the introductory slides and presentation, work through these reinforcement questions to make sure you and your team has a good understanding of replicability and the problem.
Main Analysis Template
analysis_template (Rmd) (html) : R markdown template which each team will use to create a fully reproducible analysis with the goal of assessing and interpreting the replicability of two pharmacogenomic experiments. This document will contain all of the text and code of their analyses, which are quided by a series of questions. The tools and concepts needed to answer the questions are explored in the tutorials.
Data files are included under the
rawPharmacoData.rds : raw data file generated by
downloadData.R that contains drug response data at every dose for each cell line and drug used in both studies.
summarizedPharmacoData.rds : summarized data file generated by
downloadData.R that contains drug response data (combined over all doses) for each cell line and drug used in both studies.
modelSummarizedPharmacoData.rds : summarized data file generated in the
supplement_dose_response.Rmd tutorial that contains recomputed drug response data (combined over all doses) for each cell line and drug used in both studies.
Tutorials are included under the
Each tutorial contains text and code that explores various aspects of data science, replicability, and reproducibility. Tutorial
0a provides a gentle introduction to R for those with limited programming experience, and Tutorial
0b introduces some of the main functions in the
tidyr packages. Tutorials
1b get us started with exploring the two original datasets from the CCLE and GDSC studies,
2b dig deeper into specific issues that can impact replicability and provide ideas for things to look into for this Replicathon. Finally, the Supplementary Tutorials provide more details that are useful but not immediately necessary for getting started.
0a (Rmd) (html) : “Introduction to R Basics”
0b (Rmd) (html) : “Introduction to the Tidyverse”
1a (Rmd) (html) : “Exploring Pharmacological Data with the
1b (Rmd) (html) : “Exploring Replicability with the
2a (Rmd) (html) : “Digging Deeper with Cell Line and Drug Subgroups”
2b (Rmd) (html) : “Digging Deeper with Drug Response Summarization”
supplement (Rmd) (html) : “Correlation Measures”
supplement (Rmd) (html) : “Dose-Response Modeling”
supplement (Rmd) (html) : “Exploring High Dimensional Data with PCA and Clustering”
Code to generate data files (You do not need to use this)
For full reproducibility, this is the script to generate the
RDS files. This step has already been done for you, and the data files should be available as part of this repository without running the script.
downloadData.R : a script that uses the PharmacoGx package to format two datasets (raw and summary level) and save them as
- Luli Zou
- Ana Betty Villaseñor-Altamirano
- Kelly Street
- Mercedeh Movassagh
- Jill Lundell
- Patrick Kimes
Code of Conduct
To ensure a safe, enjoyable, and friendly experience for everyone who participates, we have a strict code of conduct that all participants are expected to follow.