Data Science with R for the Life Sciences (BIOL 806)
Syllabus and Course Outline
University of New Hampshire
Fall 2021
Class Time:
Lecture: Tues 2:10-3:30pm
Lab: Thurs 2:10-3:30pm or 3:40-5:00pm
Location: Spaulding 230 at Google Map
Instructor: Dr. Easton White
Office: G44 Spaulding Hall
Office hours: TBD
Phone: TBD
Instructor Email: easton.white@unh.edu
Teaching Assistant: TBD
Office: TBD
Office hours: TBD
Phone: TBD
Course Description
Introduces students to the basic data analysis and programming tools commonly used throughout the life sciences. Students will become proficient in R programming, data wrangling and cleaning, the principles of open and reproducible science, SQL database management, version control via Git/Github, building maps, and Bash command lines. Data sets and case studies from across the life sciences (e.g., ecology, genetics, agriculture) will be used throughout the course. Each student will be certified through the Software Carpentry and Data Carpentry curriculum standards (https://carpentries.org/). The class culminates with a small group project analyzing a dataset, writing up findings in R markdown, and presenting to the course.
Course Learning Objectives
By the end of this course, students should be able to:
- Understand and implement best practices for data management
- Compare and contrast different tools for data management (Excel, SQL, etc.)
- Apply R statistical software to develop scripts for basic data cleaning and statistics
- Develop reproducible workflows for data analysis pipelines
- Build R markdown documents for visualizing data and organizing text
- Collaborate and devise version control practices using Git and Github
- Create simple Bash commands for version control
- Develop code to load, clean, and visualize simple spatial data in R
- Design and teach a lesson on a R package by implementing active learning techniques and live coding exercises
- Assemble publicly available data, design a set of analyses, and write up results in the style of a scientific paper
This is clearly a lot of concepts and skills to cover in one semester. However, there will be lots of time to ask questions and to have discussions. The format of the class will change from day to day, but will include a combination of lectures, problem sets, group activities, and demonstrations.
Any and all of the content of this syllabus is subject to change as we go through the course. The material will be tailored to fit the needs of the class. Changes will be announced in-class and electronically.
Course website
All course materials are available on the course website at: myCourses (Canvas)
Required course materials
I do not assign any textbooks for my courses. Therefore, I provide all the necessary readings (mostly peer-reviewed scientific publications) for the course and make them available online through Canvas. I will also post the lecture slides on Canvas.
All course materials (e.g., R, Git, etc.) are open-source and freely available.
Assignments and Evaluation
Lab assignments: (60%)
There will be 10 lab assignments corresponding with that week’s lecture material. Each lab assignment will consist of a series of challenges involving data sets from across the life sciences. Students will prepare their assignments using R markdown and submit them via Canvas. These will mostly be completed during class time in small groups. I have a policy of dropping the lowest score on the weekly lab assignments.
Final project (20%):
The lab assignments described above build on one another to provide all the computational skills needed to complete a stand-alone research project. The culmination of the class will result in a small group research paper using a data set of the groups choosing. Each group will also deliver a brief presentation of their paper.
Participation (10%)
Points are earned for both “in-class” discussion participation as well as discussion in online forums.
Exams (30%)
There will be three exams over the course of the semester, including the final exam. The final exam is not cumulative.
Lab (10%)
Each student will deliver one, 30-minute lecture on an R package of their choosing. Each student will be scheduled to give a presentation over the final portion of the semester (schedule TBD, but all students will have a minimum of 3 weeks between receiving feedback on their proposed topic and giving their presentation.
Grading scale
Final letter grades for Biology 412 are a composite of your lecture grade (70% weight) and lab grade (30% weight) and are not curved but based on the following grade ranges: The grading scale will follow the standard UNH percentage scale:
| Percentage | Grade |
|---|---|
| 100.00-94.00% | A |
| 93.99-90.00% | A- |
| 89.99-87.00% | B+ |
| 86.99-83.00% | B |
| 82.99-80.00% | B- |
| 79.99-77.00% | C+ |
| 76.99-73.00% | C |
| 72.99-70.00% | C- |
| 69.99-67.00% | D+ |
| 66.99-63.00% | D |
| 62.99-60.00% | D- |
| At/below 59.99% | F |
Course Policies and General Expectations
Academic Honesty and Honor Code: In all cases except for explicitly stated group work, performance on tests is to be based on individual effort, and will be graded as such. Tests are to be electronics-free; phones, tablets, ipods/pads, whatever, are expected to be put away, not visible, and not accessed during the test. Any violation of the academic honesty policy (https://www.unh.edu/student-life/09-academic-honesty) can result in an F in the class. This includes, but is not limited to: cheating on exams, using multiple clickers for absent students, submitting an assignment completed as coursework for another class (misrepresentation), and plagiarism. Particularly for laboratory reports, be aware of what plagiarism is (unattributed use of others’ ideas as your own). I encourage all of you to take the plagiarism tutorial because you are responsible for understanding what plagiarism is: https://cola.unh.edu/academics/plagiarism-tutorial.
Classroom Behavior Expectations: To ensure a climate of learning for all, disruptive or inappropriate behavior may result in exclusion (removal) from this class. As a reminder, cell phone/pda, etc. use, including text messaging, and videotaping and recording is not permitted in this class by Faculty Senate rule unless by instructor permission.
Online Assignment Policies: Some of the assignments you complete will be directly on myCourses (Canvas). It is your responsibility to check to make sure that a grade was properly recorded.
Late Work Policy: No assignments turned in late will receive credit. Instead, I have a policy of dropping the lowest scores on assignments in some categories (see Course Activities and Grading section).
Communication Policy
If you have questions about anything related to the course, please email: Easton.White@unh.edu. If you need to contact me about a personal or confidential matter (e.g., disability accommodations), please e-mail me directly. I will make every effort to answer your emails promptly, but email replies may take up to 24 hours during the week and 48 hours over the weekend.
Disability Accommodations
According to the Americans with Disabilities Act (as amended, 2008), each student with a disability has the right to request services from UNH to accommodate his/her disability. If you are a student with a documented disability or believe you may have a disability that requires accommodations, please contact Student Accessibility Services (SAS) at 201 Smith Hall. Accommodation letters are created by SAS with the student. Please follow-up with your instructor as soon as possible to ensure timely implementation of the identified accommodations in the letter. Faculty have an obligation to respond once they receive official notice of accommodations from SAS, but are under no obligation to provide retroactive accommodations. For more information refer to www.unh.edu/studentaccessibility or contact SAS at 603.862.2607, 711 (Relay NH) or sas.office@unh.edu.
Your academic success in this course is very important to me. If, during the semester, you find emotional or mental health issues are affecting that success, please contact Psychological and Counseling Services (PACS) (3rd fl, Smith Hall; 603 862-2090/TTY: 7-1-1) which provides counseling appointments and other mental health services.
The University of New Hampshire and its faculty are committed to assuring a safe and productive educational environment for all students and for the university as a whole. To this end, the university requires faculty members to report to the university’s Title IX Coordinator (Donna Marie Sorrentino, dms@unh.edu, 603-862-2930/1527 TTY) any incidents of sexual violence and harassment shared by students. If you wish to speak to a confidential support service provider who does not have this reporting responsibility because their discussions with clients are subject to legal privilege, you can find a list of resources here (privileged confidential service providers/resources). For more information about what happens when you report, how the university considers your requests for confidentiality once a report is made to the Title IX Coordinator, your rights and report options at UNH (including anonymous report options) please visit (student reporting options).