Additional Resources
This list provides some links to resources on reproducibility topics that may be useful as you develop your reproducible research skills and practices. In addition, we have curated a set of resources on our website that may be useful for starting out with R programming.
Please note, this is not an exhaustive list. It includes multiple types of resources for varying levels of experience, so we would not necessarily recommend every resource here for everyone. Resources are listed by topic and in alphabetical order, not in order of recommendation.
Table of Contents
Comprehensive Resources
- Bioinformatics Data Skills - Vince Buffalo
- Collections on Reproducibility - Nature
- Good Enough Practices in Scientific Computing - PLOS Computational Biology
- Guide for Reproducible Research - The Turing Way
- Introduction to Reproducibility in Cancer Informatics course - Informatics Technology for Cancer Research (ITCR)
- Advanced Reproducibility in Cancer Informatics course - ITCR
- Learning Bioinformatics at Home - Harvard Informatics Group
- Reproducibility 4 Everyone
- Reproducibility Standards for Machine Learning in the Life Sciences - nature
- Ten Simple Rules for Quick and Dirty Scientific Programming - PLOS Computational Biology
- Ten Simple Rules for Reproducible Computational Research - PLOS Computational Biology
- Toronto Data Workshop - Rohan Alexander
- Toronto Workshop on Reproducibility - Rohan Alexander
Git
- Happy Git and GitHub for the UseR
- Ten Simple Rules for Taking Advantage of Git and GitHub - PLOS Computational Biology
- Version control with Git - The Carpentries
- New to Git - Gitkraken
Project Organization
- Project Organization for Genomics - The Carpentries
- protocols.io
- Ten Simple Rules for Writing Dockerfiles for Reproducible Data Science - PLOS Computational Biology
- Ten Simple Rules for Writing and Sharing Computational Analyses in Jupyter Notebooks - PLOS Computational Biology