UT Biocomputing 2015

Peer-led working group in Biological Computing at UT Austin, Spring 2015

This project is maintained by sjspielman


This is the official website for the Spring 2015 Peer-led Biocomputing Group at UT Austin, offered through the Center for Computational Biology and Bioinformatics. The goal of this class is to take away any fear of programming that you may have so that computing can become an advantage rather than a barrier to your research. On Wednesdays, we will provide lessons suitable for beginners in programming. Each week you should post at least one question and answer on the UTbiocomputing google group and complete the homework. On Tuesdays we will help you with homework or if you had no problems, come anyways to meet other people that are computing at UT, and get some handy tips from GSAF's Scott Hunicke-Smith.

Please install the required software no later than the second day of class. Installation instructions are available here.


  • Rebecca (Becca) Tarvin (PAT 123) rdtarvin@utexas.edu
  • Stephanie Spielman (MBB 3.232) stephanie.spielman@gmail.com
  • Meeting Times

  • Open Coding Hour: Tuesdays 5-6pm in CCBB conference room (GDC 7.514)
  • Class: 4-5pm on Wednesdays in FNT 1.104
  • Helpful Resources

  • 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.

  • Don't forget your most valuable resource: google! If you encounter an issue, 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**](http://www.stackoverflow.com). This forum-based website has all the answers, possibly literally.

  • This wiki and this github repository contain powerpoints, exercises, and cheatsheets from the Spring 2014 course.

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

    Each item in the "Topic" column links to materials for that course day. Materials include a cheatsheet, lesson plan, and sometimes a powerpoint and/or example scripts. All course materials can also be accessed directly from this github repository.

    Week Date Topic Instructor
    Week 1 Jan 21 Welcome and Introduction Becca
    Week 2 Jan 28 UNIX and Bash: Navigating the Command Line Becca
    Week 3 Feb 04 Python I: Basic data types and structure Stephanie
    Week 4 Feb 11 Python II: Control flow and loops Becca
    Week 5 Feb 18 Python III: Functions Stephanie
    Week 6 Feb 25 Python IV: File Input/Output Stephanie
    Week 7 Mar 04 Python V: Testing and Code Hygiene Becca
    Week 8 Mar 11 Python VI: Biopython Stephanie
    Week 9 Mar 25 Merging Python and Bash Stephanie and Becca
    Week 10 Apr 01 Version Control with git Cheng Lee
    Week 11 Apr 08 Statistical Computing in R Nate Pope
    Week 12 Apr 15 Data analysis in Python Ben Liebeskind
    Week 13 Apr 22 High-performance computing with TACC Benni Goetz
    Week 14 Apr 29 RNAseq: Computational platforms and pipelines Dariya Sydykova
    Week 15 May 06 pyRAD: Pipelines for analyzing NextGen SNP data April Wright