Syllabus

Course Description

This course is meant to be a gentle introduction to data wrangling and visualization using the tidyverse in R. This course focuses on practical data science skills in R (loading data, data wrangling, visualization, automation, machine learning, and running statistical models) that you’ll use almost everyday in your work. It is meant for both beginners and students wanting to brush up on their R skills.

Credit Hours

3 credit hours.

Learning Objectives

1. Understand and utilize R/RStudio.
2. Understand basic data types and data structures in R.
3. Familiarize and load data files (Excel, Comma Separated Value files) into R/Rstudio, with tips on formatting.
4. Visualize datasets using ggplot2 and understand how to build basic plots using ggplot2 syntax.
5. Filter and format data in R for use with various routines.
6. Execute and Interpret some basic statistics in R.
7. Automate repetitive tasks in R, such as loading a folder of files.
8. Execute basic machine learning workflows using tidymodels.
9. Learn about Bioconductor Data Structures and conduct simple analysis with these structures.
10. Your Choice: shiny, leaflet or tidytext.

Course Website

All course information will be available here:

https://sph-r-programming.netlify.com/

Course discussions will be done in the class Discord Workspace. Invites will be sent before class.

Lab Assignments will be done in the class RStudio.cloud workspace. Students should register at https://RStudio.cloud before the lab. Link to join the workspace will be sent out before the first lab.

Office Hours

Office Hours will be held via Zoom and a link will be sent out that day. Feel free to drop into the office hours and work and ask questions as needed.

Prerequisites or Concurrent Enrollment Requirements

No Prerequisites

Faculty Information

Code of Conduct

This class is governed by the BioData Club Code of Conduct: https://biodata-club.github.io/code_of_conduct/

This class is meant to be a psychologically safe space where it’s ok to ask questions. We want to normalize your own curiosity and fuel your desire to learn more.

If you are disruptive to class learning or disparaging to other students, I may mute you for the day. I am very serious about this.

Required Texts or Readings

We will be drawing on the following online textbooks during class and labs. These books are online and free, though you can order them as textbooks if you prefer that format.

Getting Used to R, RStudio, and RMarkdown. Chester Ismay. https://ismayc.github.io/rbasics-book/

Introduction to Data Science. Tiffany Timbers, Trevor Campbell, Melissa Lee. https://ubc-dsci.github.io/introduction-to-datascience/

RMarkdown for Scientists. Nick Tierney. https://rmd4sci.njtierney.com/

R for Data Science. Garret Grolemund and Hadley Wickham. https://r4ds.had.co.nz/

Words of Encouragement

This was adopted from Andrew Heiss. Thanks!

I promise you can succeed in this class.

Learning R can be difficult at first—it’s like learning a new language, just like Spanish, French, or Chinese. Hadley Wickham—the chief data scientist at RStudio and the author of some amazing R packages you’ll be using like ggplot2—made this wise observation:

It’s easy when you start out programming to get really frustrated and think, “Oh it’s me, I’m really stupid,” or, “I’m not made out to program.” But, that is absolutely not the case. Everyone gets frustrated. I still get frustrated occasionally when writing R code. It’s just a natural part of programming. So, it happens to everyone and gets less and less over time. Don’t blame yourself. Just take a break, do something fun, and then come back and try again later.

Even experienced programmers find themselves bashing their heads against seemingly intractable errors. If you’re finding yourself taking way too long hitting your head against a wall and not understanding, take a break, talk to classmates, e-mail me, etc.

LeaRning is Social

The students who have a bad time in my workshops and courses are the ones who don’t work with each other to learn. We are a learning community, and we should help each other to learn.

If you understand something and someone is struggling with it, try and help them. If you are struggling, take a breath, and try to pinpoint what you are struggling with.

Our goal is to be better programmers each day, not to be the perfect programmer. There’s no such thing as a perfect programmer. I’ve been learning new things almost every day.

Attendance Requirements

Online attendance is required. Please let me know in advance if you have to miss class, or if you have an emergency.

Classes will be recorded, but please do not use this as an excuse to miss class. Again, those who are curious and ask questions will learn quite a bit.

Grading Policy

• Attendance 10%
• Midterm Project 15%
• Function of the Week 5%
• Homework Assignments 45%
• Final Project 25%

Copyright Information

Every reasonable effort has been made to protect the copyright requirements of materials used in this course. Class participants are warned not to copy, audio, or videotape in violation of copyright laws.

Journal articles will be kept on reserve at the library or online for student access. Copyright law does allow for making one personal copy of each article from the original article. This limit also applies to electronic sources.

To comply with the fair use fair use doctrine of the US copyright law, Sakai course sites close three weeks after grades are posted with the Registrar. Please be sure to download all course material you wish to keep before this time as you will have no further access to your courses.

Communication Policy

1. If the syllabus directs the student to contact the TA before contacting the instructor, the student should do so. Otherwise, the student should contact the instructor and allow 2 business days (not including weekends) for a response.

2. If the student does not receive a response from the instructor within 2 business days, s/he should contact the TA (if there is one). When contacting the TA s/he should cc the instructor and Diane Doctor at doctord@ohsu.edu.

3. If a student does not receive a response from the TA within 1 business day (not including weekends), s/he should contact Diane Doctor at doctord@ohsu.edu and cc the instructor and the TA.

4. If Diane does not reply within 1 business day (not including weekends), the student should contact Andrea Ilg at ilgan@ohsu.edu.

5. Students having difficulties with Sakai should contact the Sakai Help Desk at sakai@ohsu.edu or at (877) 972-5249. Sakai help is available M-F from 8am to 9 pm and weekends from Noon to 5pm. Do not contact the instructor.

6. Please use professional etiquette when communicating with peers and the instructor. This means avoiding aggressive or offensive language, showing respect for others’ opinions and positions, and conducting yourself as if you were face to face with them. Please pay special attention to etiquette in class forums and when using email. If you notice someone violating this policy, please make the instructor and TA aware of the problem.

Syllabus Changes and Retention

This syllabus is not to be considered a contract between the student and the School of Medicine. It is recognized that changes may be made as the need arises. Students are responsible for keeping a copy of the course syllabus for their records.

Syllabus Statement Regarding Disability Services

OHSU is committed to providing equal access to qualified students who experience a disability in compliance with Section 504 of the Rehabilitation Act of 1973, the Americans with Disabilities Act (ADA) of 1990, and the ADA Amendments Act (ADA-AA) of 2008. If you have a disability or think you may have a disability (physical, sensory, chronic health, psychological or learning) please contact the Office for Student Access at (503) 494-0082 or studentaccess@ohsu.edu to discuss eligibility for academic accommodations. Information is also available at www.ohsu.edu/student-access. Because accommodations may take time to implement and cannot be applied retroactively, it is important to have this discussion as soon as possible. All information regarding a student’s disability is kept in accordance with relevant state and federal laws.

Commitment of Equity and Inclusion

Oregon Health & Science University is committed to creating and fostering a learning and working environment based on open communication and mutual respect. If you encounter sexual harassment, sexual misconduct, sexual assault, or discrimination based on race, color, religion, age, national origin or ancestry, veteran or military status, sex, marital status, pregnancy or parenting status, sexual orientation, gender identity, disability or any other protected status please contact the Affirmative Action and Equal Opportunity Department at 503-494-5148 or aaeo@ohsu.edu. Inquiries about Title IX compliance or sex/gender discrimination and harassment may be directed to the OHSU Title IX Coordinator at 503-494-0258 or titleix@ohsu.edu

Academic Honesty

Course participants are expected to maintain academic honesty in their course work. Participants should refrain from seeking past published solutions to any assignments. Literature and resources (including Internet resources) employed in fulfilling assignments must be cited. See http://www.ohsu.edu/xd/education/library/research-assistance/plagiarism.cfm?WT_rank=1# for information on code of conduct for OHSU and

http://www.ohsu.edu/xd/education/teaching-and-learning-center/for-students/index.cfm for more information on citing sources and recognizing plagiarism.

In an effort to uphold the principles and practice of academic honesty, faculty members at OHSU may use originality checking systems such as Turnitin to compare a student’s submitted work against multiple sources.

To protect student privacy in this process, it will be necessary to remove all personal information, i.e. student name, email address, student u-number, or any other personal information, from documents BEFORE submission.

Use of Sakai

This course will have an online component, which can be accessed through Sakai, OHSU’s online course management system. For any technical questions or if you need help logging in, please contact the Sakai Help Desk.

Hours: Sakai Help Desk is available Mon – Fri, 8 am – 9 pm and weekends 12 pm – 5 pm, Pacific Time.

Contact Information:

(Toll-free) 877-972-5249

(Web) http://atech.ohsu.edu/help

(Email) sakai@ohsu.edu

OHSU Proctoring Policy

It is OHSU policy that any exam offered online and worth more than 10% of the final course grade must be virtually proctored. In this course, we will be using the services of Examity, a remote proctoring services. You will be required to schedule your exam three (3) weeks ahead of time. There is no cost to the student. More information will be provided to you regarding setup, scheduling, and requirements in the Course Materials.

Policy number: 02-70-050 (http://www.ohsu.edu/xd/education/student-services/academic-programs-and-assessment/academic-policy/approved-policies/upload/Online-Exam-Proctoring-02-70-050.pdf)

Inclement Weather Policy

When the weather forecaster is calling for ice or snow, call the OHSU Alert Line, 503 494-9021, for information regarding weather conditions that may affect operations at OHSU. This hot line will offer specific recorded messages for road conditions on OHSU's Marquam Hill and West campuses (option 1), and for patients (option 2), students (option 3) and employees (option 4).

If extreme weather conditions present potentially unsafe situations, the provost of the university may choose to delay or cancel classes, or alter office and research activities. If classes are canceled or delayed, residents and students who have patient care responsibilities must meet those obligations.

For more information, please view the website http://www.ohsu.edu/xd/about/visiting/weather/index.cfm or call the above hotline.