Course Syllabus

CSE284 Winter 2024 Syllabus

Instructor: Dr. Melissa Gymrek, mgymrek@ucsd.edu

TAs: Divya Prabhu dprabhu@ucsd.edu, Denghui Chen (Den) dec037@ucsd.edu, Mihika Sonalkar msonalkar@ucsd.edu 

Lectures: TR 3:30-4:50 pm (FAH 1101) (zoom link)

Office Hours:

• Melissa: Fridays 12-1 pm, FAH 4307
• Den: Tuesdays and Thursdays, 1-2 pm, BRF2 4A04 or Zoom
• Divya: Wednesdays, 4-6 pm, Zoom
• Mihika: Fridays, 4-6 pm, EBU3B Basement B270A or Zoom

Private appointments to discuss accommodations or special circumstances can be arranged by email.

Course Description

Genome-sequencing is quickly becoming a commodity, and millions of people have already analyzed their own genomes through direct-to-consumer companies. This course provides an introduction to current bioinformatics techniques for analyzing and interpreting human genomes. We will learn how to interpret a single genome in the context of an entire population. Topics covered include an introduction to human medical and population genetics, human ancestry, finding and interpreting disease-causing variants, genome-wide association studies, and genetic risk prediction. We will also discuss the social impact of the personal genomics revolution.

Prerequisites

There are no official prerequisites for this course, but it is assumed students have some programming experience with Python and are familiar with using the UNIX command line.

Course objectives

Through this course students will:

• Gain basic bioinformatics skills needed to analyze a personal genome using the UNIX command line.
• Gain the ability to critically read and interpret basic science and translational literature relevant to personal genomics.
• Demonstrate knowledge and understanding of the social impacts of the personal genomics revolution.
• Gain skills and experience necessary to carry out original research related to personal genomics.

Course structure

The course will consist of 4 modules (Intro, ancestry, complex traits, and special topics). We will have problem sets due every other week, with roughly one problem set per module. Problem sets will be completed on JupyterHub, and will consist of a mixture of programing assignments and short answer questions. On weeks where problem sets are not due, there will be a short online assignment (completed on Canvas) with questions about required readings. The course will end with a final project, in which students will work in groups to implement one of the computational methods we learned about in the course.

Course sessions

Class meetings will typically consist of a lecture (~45 minutes) followed by an interactive group activity.  In-person attendance is strongly encouraged to get the most out of these group exercises.

Genotyping FAQ

The goal of this course is to teach you how to analyze your genome. At this time, we are not able to provide genotyping or sequencing services to students, and instead homeworks will be performed on publicly available human genomes. You are welcome to analyze your own genome using a direct-to-consumer service such as 23andme or Ancestry.com. You will also get access to a range of fun tools on their website that will complement some of the analyses we do in class. Multiple homework assignments are built to analyze the type of data available from 23andme.

Please keep in mind the following:

• It is NOT required that you analyze your own genome. Your grade is in no way influenced by whether or not you participate in 23andme.
• To ensure the previous point, you do not need to tell me if you will be analyzing your own genome.
• If you do 23andme, it is at your own risk and at your expense. We do not have funding to pay for the test.
• While you are free to analyze your genome, you must still complete the homework assignments with the provided genomes as well.
• 23andme can take up to six weeks, so sign up early if you want to use it during class.

Grading

Your grade will be based on:

• Problem sets (50%)
• Reading questions (15%)
• Final project (proposal 5%, peer review 5%, report+code 20%, presentation 5%)

All assignments (problem sets and reading questions) will be due on Fridays at 11:59pm.

There will be a total of 4 problem sets. PS1 is very short and worth 5%. The other three problem sets are worth 15% each. Problem sets are graded out of 100 points. Late problem sets will lose five points for each day past the due date. This is capped at one week past the due date, at which point you can no longer turn in the assignment for credit.

There will be three short "quizzes" with questions on required readings, worth 5% each. These can be completed asynchronously any time before the due date.

See final project guidelines for more info on projects.

Final grades will be out of 100 points. ≥70 points is passing. If you are taking the course for a letter grade, we will use the following scale: A+:100+, A:93-99, A-:90-92, B+:87-89, B:83-86, B-:80-82, C+:77-79, C:73-76, C-:70-72, F:0-69.

Academic integrity

While working on assignments you are encouraged to chat with your classmates, look things up online, and ask instructors for help. DO NOT directly copy/paste code to/from other students in the class or websites. DO NOT post questions about assignments on sites like seqanswers or stack overflow (you can research existing threads on these sites, just don't start new ones for the coursework). 

Accommodations for students with disabilities

If you have a disability for which you are or may be requesting accommodations, please contact the Office for Students with Disabilities. You must have documentation from the the Office before accommodations can be granted.

Diversity and inclusion

We are committed to fostering a learning environment for this course that supports a diversity of thoughts, perspectives and experiences, and respects your identities (including race, ethnicity, heritage, gender, sex, class, sexuality, religion, ability, age, educational background, etc.). Our goal is to create a diverse and inclusive learning environment where all students feel comfortable and can thrive.

Our instructional staff will make a concerted effort to be welcoming and inclusive to the wide diversity of students in this course. If there is a way we can make you feel more included please let one of the course staff know. Our learning about diverse perspectives and identities is an ongoing process, and we welcome your perspectives and input.

We also expect that you, as a student in this course, will honor and respect your classmates, abiding by the UCSD Principles of Community (https://ucsd.edu/about/principles.html). Please understand that others’ backgrounds, perspectives and experiences may be different than your own, and help us to build an environment where everyone is respected and feels comfortable.

If you experience any sort of harassment or discrimination, please contact the instructor as soon as possible. If you prefer to speak with someone outside of the course, please contact the Office of Prevention of Harassment and Discrimination: https://ophd.ucsd.edu/.

Disclaimer

While we have every intention of following this syllabus, any information here is subject to change.