Building Skills in Quantitative Biology

Abstract

Quantitative skills are essential for biological research. We consider such skills to include the computational, statistical and mathematical techniques used to study life and living organisms, including aspects of big data, transparency and reproducibility in science. However, the breadth of quantitative techniques now employed in biology make it very likely that there may be no suitable local expertise within a student’s home institution or a biologist’s workplace.

This e-book consists of five independent chapters or “modules” designed to teach different quantitative skills to graduate students and biologists working in academia, government agencies and private organizations. A key theme is that while the techniques presented are from various disciplines (such as computer science, statistics and mathematics), they are presented in a way that is suitable for a biological audience. Our examples and approach reflect our personal use of these tools as researchers in biology.

Each module is designed to quickly get you up and running on the topic of interest in 3-5 hours. As such, these materials should be thought of a basic introduction. We provide pointers to more advanced materials, but our aim is to “jump-start” your use of these tools. On the other hand, these modules are not designed for absolute beginners. With the exception of the module on Git and Github, the materials are written assuming that learners have some basic familiarity with R, and a standard undergraduate background in calculus and univariate statistics.

Because the modules are designed to be independent (i.e., you don’t have read the whole e-book!), you can select subtopics that are directly relevant to your research. Our hope is that this approach will simultaneously provide more targeted training and reduce the time commitment that would be involved in more generalized formal courses. Pick and choose what you need!