University of California, San Diego (UCSD)
Winter 2023
CMM262/BIOM262 is designed to teach experimental and analytical approaches in modern genetics and genomics, from experimental design through data analysis in each of several topic areas. Students will come away with an intuition and basic understanding of the function of many computational tools, including their design limitations. Because this course includes computational workshops in almost every class session, it is highly recommended that students have previous experience in at least one of the programming languages we will use (Python, Bash, or R).
🏁 Note: This 4-unit course is a core requirement for students in the UCSD Genetics Training Program (http://genetics.ucsd.edu/).
Instructor: Dr. Alon Goren (agoren@ucsd.edu)
Teaching Assistant 1: Hannah Mummey (hmummey@ucsd.edu)
Teaching Assistant 2: Arya Massarat (amassara@ucsd.edu)
Teaching Assistant 3: Daniella Vo (dtv004@ucsd.edu)
Teaching Assistant 4: Jeff Jaureguy (jjauregu@ucsd.edu)
As each module is taught by a separate lecturer, their contact information is provided in the syllabus table at the following Google Sheets link:
https://docs.google.com/spreadsheets/d/1s-kjGqblJmk4cW-RhUNh_JHS_vk_nCP9CumVm6JsTSI
⚠️ Note: We will be using Slack as our primary method of communication for this course!
You can join our group using the Slack link sent out in our first Canvas announcement.
Students should have at least an introductory knowledge of genetics, so classes in genetics are listed as official prerequisites for the course.
In addition, it is absolutely crucial that students have at least some introductory experience with a programming language, preferably R or python. During the first week of class, we will review R, python, and bash. But after the first week, we'll immediately dive into complex usage of all three. Thus, the first week should serve more as a review than a comprehensive tutorial.
Take a look at our course material from last year to gauge the level of programming experience required. If you think you might need to refresh yourself, here are some resources:
- A book introducing R for data scientists
- A crash-course book for python
- A book that explains how to use data science libraries in python
Classes are on Tuesday and Thursday from 9:00 AM - 11:50 AM PST.
Lecture recordings for each week will be posted on Friday morning. You can find recordings of the lectures here: https://drive.google.com/drive/folders/1tzSEuG0XR0Jaz7Ilp7uiImW97z7IH55n
Slides for each lecture will be attached to a README.md file within each module folder.
Office hours usually take place via Zoom from 4-5 pm on Mondays. The zoom link will be shared internally with the class on our slack!
Two Mondays this quarter will be holidays. During those weeks, office hours will be held on Wednesday at 4-5pm instead. This includes:
Wednesday: Jan 18th 4-5pm
Wednesday: Feb 22nd 4-5pm
You will be able to find all homework assignments for this course on the github, in the hw directory. Exams materials will be shared via Gradescope. You will also be able to find all of the necessary materials for each assignment on the UCSD Jupyterhub (Data Science) Platform if you're officially enrolled. The Jupyterhub can be found here: https://datahub.ucsd.edu/hub/login
We'll be using Gradescope for submitting the homework assignments, as well as the midterm and final exams. If you have not been added to the course, to sign up for Gradescope, please follow the steps outlined below:
- Navigate to the Gradescope Website at https://www.gradescope.com/
- Select the link in the header to "Sign Up", and then select the option to sign up as a "Student"
- Enter the following Course Entry Code:
BBR48B - Input your Full Name, UCSD Email, and UCSD Student ID (should be A#######); Note: If you are auditing the course, please enter AUDITOR as your Student ID
- Select "Sign up as Student" to complete the sign-up process, and then check the email you have provided for the link to set your password and log in information
Homework will be assigned on Thursdays and due on the following Thursday throughout the quarter. There will not be an assignment every week. Assignments will be announced in the week they are assigned. Submission of homework will be conducted through GradeScope and will be due by 9:00 AM PST on Thursday mornings.
- Midterm Examination:
- Released on 2/16/23
- Submission via Gradescope on 2/23/23 by 9:00 AM PST
- Final Examination:
- Released on 3/14/23
- Submission via Gradescope on 3/21/23 by 11:59 PM PST
If for whatever reason you cannot deliver an assignment by its associated due date, you should inform the course instructor and TAs at least a day before the due date. For each late submission 10% of the maximal number of points is deducted for every day or part of a day that an assignment is handed in late.
Note: We know that things happen!
If you're experiencing a health or family emergency, please let the course instructors and teaching assistants know and we can work something out!
We recognize that small mistakes can sometimes propagate into large points deductions on assignments. When grading, we try to award partial credit whenever possible. However, for students that submit homework assignments with large mistakes, we will allow one homework regrade throughout the quarter for full credit back.
In order to qualify for a regrade, a student must score below 80% on the assignment and they must resubmit within one week of when the assignment's grades were published.
| Percentage | Category |
|---|---|
| 55% | Homework |
| 20% | Midterm |
| 20% | Final |
| 5% | Participation |
Letter grades are assigned based on the following scale:
| Grade | Lowest Percentage |
|---|---|
| A+ | 97% |
| A | 93% |
| A- | 90% |
| B+ | 87% |
| B | 83% |
| B- | 80% |
| C+ | 77% |
| C | 73% |
| C- | 70% |
| D | 60% |
| F | 0% |
Participation grades will be given based off of attendance, class participation, and number of weekly surveys completed.
This course is designed to be highly interactive, so we greatly appreciate your participation and engagement with the material and class sessions. We would like to show respect for all instructors, especially those volunteering their time to be guest lecturers, by engaging with their content.
There will be a feedback survey posted to Canvas on Thurs at 9:00 am each week. Please fill them out by the next Tues at 9:00 am. We really value your feedback! It helps us improve the modules each year.
We will allot students at most three passes to submit surveys late, by the end of the quarter. We will subtract 5% from your participation grade for every additional survey (beyond the first three) that are submitted late.
To receive late credit for a survey, you must submit it by March 17, 2023 at 11:59 pm.
Plagiarism will not be tolerated. Do not copy and paste answers from the internet, and make sure all answers on homework and exams are completely in your own words.
Questions may be discussed with classmates but all work must be done individually.
Please use office hours for questions regarding the homework assignments or take-home exams. It can be difficult, especially with code and software, to troubleshoot your problems via email or slack. If you are unable to attend office hours, you are welcome to contact the TAs with your questions via email or slack.
⚠️ Note: Please make sure to include all TAs in your correspondences so we can ensure that you get help as soon as possible.
If you must email or slack regarding a question, please do not expect a response unless it is within working hours (Monday-Friday, 8:00 AM - 8:00 PM PST), otherwise, there is no guarantee you will receive a response.
You can find the schedule of what we'll be covering day-by-day at the following Google Sheets link:
https://docs.google.com/spreadsheets/d/1s-kjGqblJmk4cW-RhUNh_JHS_vk_nCP9CumVm6JsTSI
Try the suggestions in this doc and see if they help:
https://docs.google.com/document/d/1OXpPzo50UU_bUY6mrmZ5gNq7_jjD1nUEP1Rw3jkHQmw
You will lose access to DataHub at the end of the spring quarter of this year, but you can download all of your materials before that happens! Follow these instructions to retain access to all of your work.
Alternatively, you can request an extension to your access here.