Resources

We have compiled a list of resources that may be of use as you learn programming:

• Google is your most valuable resource. We cannot emphasize this enough!! If you encounter an issue (e.g. error message), chances are somebody else has also encountered it and has asked about it. Googling your error messages is one of the best debugging strategies there is. In particular, try to find links to the website stackoverflow.com. This forum-based website has all the answers, possibly literally (although they may be snarky).


• We strongly recommend the book Practical Computing for Biologists by Haddock and Dunn. The book provides a really thorough overview of most of what we'll learn in this class (including Unix, Python, R, , and more! The book's accompanying website (linked above) is also regularly maintained with important tips, examples, and errata.


• The UNIX Tutorial for Beginners is a great resource and starting point for getting comfortable with the command-line environment.


• Materials from the 2015 Spring Biocomputing course can be found here.


• Materials from the 2015 CCBB Big Data in Biology Summer School "Introduction to Python" course can be found here. In addition, the book's appendix, which contains "cheatsheets" for regular expressions, Bash/UNIX, Python, and SQL is available for download here.


• Here's a great paper on Best Practices in Scientific Computing.


• Here's a great paper on Using python for Biocomputing.


• This website contains material which will appear in an upcoming book "R for Data Science", and currently contains some excellent and concise tutorials and exercises for using R to cleanly analyze datasets.


• This PLoS Comp Biol article, "A Quick Introduction to Version Control with Git and GitHub" provides a clear and thorough overview of using version control for research.