Fall 2023

Tuesdays 3:00-4:20 PM, Conor Auditorium FLTC

Sep 5 – Dec 5, NO CLASS on Oct 10 and Nov 21



Instructors: Tychele N. Turner, Ph.D. and Mike White, Ph.D.

Instruction Assistants: AJ Frederico, Alice Kao

Instructor/course admin contact: bio5075-admin@lists.genetics.wustl.edu

Work in the life sciences increasingly relies on large scale, quantitative data that requires basic computational and statistics skills. This course is an introduction to basic Python and statistical concepts used in molecular genetics and genomics, aimed at first-year DBBS students. The format emphasizes practical problem-solving skills by teaching both core statistical concepts, such as hypothesis testing, confidence intervals, bootstrap simulation, and power analysis, as well as computational methods to implement them. The goal of the course is to prepare students for more advanced coursework, as well as self-teaching during their research careers.

We are not all statisticians and computational biologists, but every biomedical scientist needs to develop and maintain a computational and statistical toolkit. Today, even scientists who spend much of their time at the bench will use and generate quantitative data, often at genome scale and single-cell resolution. We all need to read and evaluate papers that present analyses of these data. A computational and statistical toolkit is necessary to function competently as a modern biomedical scientist.

Building that toolkit is something that you will do throughout your graduate training and beyond. The purpose of this course is to get you started. You will learn some core coding and statistical skills, and most importantly, develop a foundation from which you can continue to learn as you build your toolkit throughout your career.

Required Software

For this class you will need a laptop with Python and Jupyter Notebook installed. Python and Jupyter are free and can be installed in various ways. The easiest way to install the required software is to download the free Anaconda Distribution, available for Windows, Mac, and Linux. Other installations are also acceptable, including miniconda and miniforge. Experienced Mac users may want to install miniforge or miniconda via the Homebrew package manager.

You will need to bring your laptop to class. If you are an enrolled student and need to borrow a laptop for the class, please contact the instructors at bio5075-admin@lists.genetics.wustl.edu (We cannot lend laptops to auditing students.)

AI-assisted coding: New this year! For many portions of this course students are permitted to use AI coding in their work. ChatGPT is one option, but it is frequently unreliable. We recommend that students sign up for a free GitHub Global Campus account. (If you already have a regular GitHub account, just use that account to sign up for Global Campus.) This will give you access to the GitHub co-pilot AI assistant. GitHub will ask you to submit a student ID to confirm your academic status. We encourage you to sign up for this service before the course starts.

Pre-course work for students without prior Python experience

Prior experience with Python or any programming language is not a pre-requisite for this course. However, we cover basic Python quickly in order to have time to discuss more advanced topics that will enable students to apply their coding skills to problems in their research. For those with no prior experience with Python, we strongly recommend  completing a Python tutorial before the course begins. This should take you no more than 10-15 hours over 3-4 weeks, and probably less. We suggest completing one of the options below:

  1. A Byte of Python (web tutorial). Work from the beginning through at least the ‘Data Structures’ chapter. Type the code as you read – don’t just read the text.
  2. Python for Everybody (web tutorial). Complete chapters 1-5. Type the code as you read – don’t just read the text. Complete the exercises.
  3. edX Programming for Everybody (online course): Programming for Everybody (Getting Started with Python)Enroll in the free version and complete the first three sessions. While the edX class might say that classes begin on a certain day, in our experience you can take this course at any time and at your own pace.