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Genomics Spring 2024 Course Description
This course is designed for beginning students who want to become familiar with the basic concepts and applications of genomics. The course covers a wide range of topics including how genomes are mapped and sequenced as well as the latest computational and experimental techniques for calling genomic variants, epigenetic changes like DNA methylation and accessible chromatin, and inferring transcription factor binding sites and motifs. High throughput techniques for ascribing function to DNA, RNA, and protein sequences including single-cell RNA-seq, whole genome sequencing, massively parallel reporter assays, chromosome conformation capture (Hi-C) analysis, and metagenomics will also be discussed. Finally, the use of genomic techniques and resources for studies of human disease will be discussed.
A heavy emphasis will be put on students acquiring the basic skills needed to navigate databases that archive sequence data, expression data and other types of genome-wide data. Through problem sets the students will learn to manipulate and analyze the large data sets that accompany genomic analyses by writing simple computer scripts. While students will become sophisticated users of computational tools and databases, programming and the theory behind it are covered elsewhere, in Michael Brent’s class, Bio 5495 Computational Molecular Biology.
Because of limited space in our teaching lab, enrollment for lab credit will be limited to 30 students. Priority will be given to students in the DBBS program. Others interested in the course may enroll for the lectures only. If you have previous experience in computer programming, we ask that you do not enroll for the laboratory credit. Prereqs, Molecular Cell Biology (Bio 5068), Nucleic Acids (Bio 548) or by permission of instructor. To enroll in just the lecture section, register for 3 credits. To enroll in both the lecture and lab sections, register for 4 credits. Credit variable, max 4 units.
Lectures
Mon, Wed 10:00-11:30am
Computer Lab
Fri 10:00-11:30am
Late penalty: 50% per day
NO EXTENSIONS
Course Directors
Ting Wang, twang@genetics.wustl.edu, room 5211, Couch Research Building, 4515 McKinley Ave.
Sheng Chih (Peter) Jin, jin810@wustl.edu, room 6213, Couch Research Building, 4515 McKinley Ave.
Teaching Assistants
Cameron Ortiz, Jenna Ulibarri, Justin Chen, Qinglin Zeng, Titi Akinwe
Please post questions on Piazza or use this email to contact the TAs: genomics.bio5488@gmail.com
TA Office Hours
Fri 10:00-11:30am (Holden Auditorium, FLTC)
Discussion Forum
Piazza
Textbooks and Resources
Although there will be a heavy emphasis on bringing students up to speed in the computational skills necessary to analyze genome-wide data, we do not assume that students have extensive computer skills. Those students who are not familiar with command line operating systems (Unix, Linux) or basic programming should should look through John McCutcheon’s Linux Primer.
Here is a quick unix reference sheet.
This class will teach students to write simple scripts using Python.
This year the course format has changed, so besides the VPN, you will not need to install additional software for the course. If you are connected to washu wifi, either eduroam or WUSM-secure, you will not need to use the VPN. Instructions for downloading and installing the VPN can be found here: vpn-Windows-all-11.16.23.pdf | Powered by BoxLinks to an external site.
The lab server is hosted through RIS/OOD which is an interactive web-browser interface that connects to remote computer resources. This allows us to host the course materials, software and code environments in one space without additional programs. In the past, students needed to download Python/Jupyter, RBase/RStudio, & additional software needed to interface with the server. Please try to connect to the remote server before class on Friday. Instructions can be found here: Compute Quick Start — RIS Services User Manual documentation.
Assignment Policies
Please see this link for assignment policies.
Syllabus
Link to syllabus.