Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

R for Reproducible Scientific Analysis #63

smcclatchy opened this issue Feb 23, 2018 · 0 comments

R for Reproducible Scientific Analysis #63

smcclatchy opened this issue Feb 23, 2018 · 0 comments


Copy link

smcclatchy commented Feb 23, 2018

The goal of this workshop is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis. The emphasis of these materials is to give participants a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. This workshop meets the prerequisite for Quantitative Trait Mapping on March 20-21.

Please visit the workshop website for more information.
You can preview the lesson to learn more about content.
Please install R and RStudio on your laptop prior to arrival.

We'll meet in the breezeway bioinformatics training room from 9am to 4:30pm on Wednesday and Thursday, March 14-15th. JAX employees can find the bioinformatics training room in building 1, unit 5 on this campus map. Visitors should bring photo ID and meet at the visitor entrance by 8:30am.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
None yet
None yet

No branches or pull requests

1 participant