Bioinformatics for Evolutionary Biology
The purpose of this course is to provide graduate students with the theoretical knowledge and practical skills for the evolutionary analysis of next generation sequence data. The course will entail data retrieval and assembly, alignment techniques, variant calling, gene expression analyses, hypothesis testing, and population genomic. The course will be presented as a series of short lectures and lab exercises over a one week period in October 2023.
This year, the workshop runs from 23rd October 2023 - 27th of October. There are two sessions a day, from 10am to Noon and from 2pm to 4pm.
The course will be run in person on the UBC campus in Biological Sciences building Rm 2139.
Tom Booker, Julia Kreiner
A mix of lecture and lab exercises, running in a 2-hour block.
The course material is organized in several topics, with slides and coding examples given in each. Typically we have a lecture for the first half of each class and a practical session for the second.
Students should have basic knowledge in R and some command line knowledge (although the latter could be obtained during the course)
To get up to speed on working with a Unix system, we recommend having taken the equivalent of Introduction to the Command Line for Genomics from Data Carpentry.
For a handy reference of common Unix commands check out the unix help file. There are some resources there that will help you find the specific command you need for each task.
Your mark will reflect participation in class (discussions and lab exercises etc) as well performance on a final assignment. The breakdown is 80% of your mark will come from participation and 20% from the assignment.
At the end of the week you will be given details of an assignment in class that combines different aspects of the work you’ll do throughout the week.
In previous years, there have been other topics that were included in the workshop as well as brief tutorials on other aspects of bioinformatics. In this section we include the slides and materials for those topics for those who are interested:
In this workshop we make use of simulated datasets for all of the tutorials and demonstrations. The simutions model a populations of Chinook Salmon living in the Fraser River in Southern British Columbia. We use a population genetic simulation modelling local adaptation to varying environmental conditions. These simulations are used to generate DNA and RNA sequence data that we use to demonstrate bioinformatic principles and give workshop participants experience using standard tools. The biggest benefit to using simulations is that we can compare bioinformatic estimates to a ground truth, which is not possible when using real data.
The GitHub page for Chinook is here: https://github.com/TBooker/Chinook
You may use your internet connection to browse this site, or you may download the entirety of the files on the site in one constantly updated zip archive here
This method dosesn’t require git, however, you’ll have to manually
update the files this way (by downloading the whole repo again).
To obtain to all the files via git, type:
git clone https://github.com/UBC-biol525D/UBC-biol525D.github.io.git
To update the all the files at any point in the future, change to the biol525D directory that was created by the previous command and type:
git pull
You may use any of the materials provided here, and modify them in any way, provided there is appropriate attribution according the license found below and included with this project.
Copyright (C) 2015 S. Evan Staton, Sariel Hubner, Sam Yeaman
Modified work (c) 2016, 2017, 2018 Gregory Owens, Kathryn Hodgins
Modified work (c) 2019 Gregory Owens, Kathryn Hodgins, J.S. Legare
Modified work (c) 2020 Kathryn Hodgins, Julia Kreiner, Tom Booker
Modified work (c) 2021 Tom Booker, Julia Kreiner
Modified work (c) 2022 Tom Booker, Julia Kreiner
This program is distributed under the MIT (X11) License, which should be distributed with the package. If not, it can be found here: http://www.opensource.org/licenses/mit-license.php
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