Genomics Spring 2023 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.
Mon, Wed 10:00-11:30am
Late penalty: 50% per day
Dian Li, Douglas Abrams, Juanru Guo, Kartik Singhal, Mariam Khanfar
Please post questions on Piazza or use this email to contact the TAs: firstname.lastname@example.org
TA Office Hours
Fri 10:00-11:30am (Holden Auditorium, FLTC)
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.
Please install software as instructed prior the first lab section if you are planning to take it.
Please see this link for assignment policies.