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BIO A 469: Human Population Genetics Computer Lab. Autumn 2023

Instructor: Darryl J. Holman

Email: djholman@u.washington.edu
Voice: 206-543-7586
Fax: 206-543-3285

Office: Department of Anthropology, Denny M237

Course Information, Autumn 2023

Scope

This course is a companion to BIO A 482 Human Population Genetics. It expands on BIO A 482 through computer laboratory sessions for exploring ideas and implementing some of the concepts presented in that course. This will be accomplished using numerical experiments, including analytical exercises, microsimulation, and visualization. We will apply some of the methods through data analysis and statistical inference. Finally, some more advanced tools used for things like phylogenetic analysis, linkage disequilibrium, and genome wide association studies will be introduced.

What will this course do for you? (1) Solidify your understanding of the genetic basis of evolution. (2) Give hands-on experience with tools and analytical methods used for teaching and doing research in human population genetics. (3) Provide experience with scientific programming, data analysis, and statistics in the R language.

Classes

MWF, 2:30pm-3:40pm, Savery (SAV) 121. Please bring a scientific calculator to class and be prepared to use it.

Office Hours

New office hours from 16-Oct-2023: I will hold Zoom office hours Tuesdays 6:00pm-7:00pm.

I will hold Zoom office hours Tuesdays 9:00am-9:50am. Contact me to set up an appointment outside these times.

Textbooks and Readings

There are no additional textbooks required for this course. Many labs will involve explorations of or application to the material found in the weekly readings for BIO A 482.

Additional readings on anthropological topics will supplement the text and will be assigned during the quarter. These readings will highlight some methods, tools, and techniques relevant to our lab sessions, as well as introducing you to some of the more advanced methods that we cannot cover in this course.

Grading

There will be 5 problem sets that will make up 25% of your final grade. A final project will make up 75% of your final grade.

Problem sets

Five problem sets will be assigned over the quarter. Each problem set is worth about 5% of your final grade. The problems will typically require some computer-based programming or analysis. You may work with others on your homework. Problem sets will typically be handed out on Wednesday and are due at the start of class on the following Wednesday unless otherwise noted in the syllabus. Problem sets must be turned in on paper.

In part, the problem sets test your ability to do the work under time constraints. Therefore, the grade of a late problem set will depreciate by 10% per day, including any fraction of a day late. For example, a problem set that would have gotten a 95% would depreciate to 95×0.9=85.5% for being one day late, 95×0.92=77% for 2 days late, 95×0.93=69% for day 3 and so on.

Project

Teams of 2 students will develop a project and make a brief (12 minute) presentation during the final exam period. More information about the projects and the format will be given out later in the term.

There are at least three types of projects possible that make use of the concepts from this course: (1) Analysis and interpretation of a genetic dataset, (2) Develop a simulation of some genetic system, (3) development of an educational tool for teaching human population genetics. Feel free to discuss other project ideas with me.

Exams

There are no exams in this course.

Course Policies

Academic misconduct

The university's policy on plagiarism and academic misconduct is a part of the Student Conduct Code, which cites the definition of academic misconduct in the WAC 478-121. According to this section of the WAC, academic misconduct includes: "Cheating"-such as "unauthorized assistance in taking quizzes", "Falsification" "which is the intentional use or submission of falsified data, records, or other information including, but not limited to, records of internship or practicum experiences or attendance at any required event(s), or scholarly research"; and "Plagiarism" which includes "[t]he use, by paraphrase or direct quotation, of the published or unpublished work of another person without full and clear acknowledgment."

The UW Libraries have a useful guide for students here.

Accommodation

Your experience in this class is important to me. If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to me at your earliest convenience so we can discuss your needs in this course. The website for the DRO provides other resources for students and faculty for making accommodations.

Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW's policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy. Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form.

Inclusion

Among the core values of the university are inclusivity and diversity, regardless of race, gender, income, ability, beliefs, and other ways that people distinguish themselves and others. If any assignments and activities are not accessible to you, please contact me so we can make arrangements to include you by making an alternative assignment available.

Learning often involves the exchange of ideas. To include everyone in the learning process, we expect you will demonstrate respect, politeness, reasonableness, and willingness to listen to others at all times-even when passions run high. Behaviors must support learning, understanding, and scholarship.

Preventing violence is a shared responsibility in which everyone at the UW plays apart. If you experience harassment during your studies, please report it to the SafeCampus website (anonymous reports are possible). SafeCampus provides information on counseling and safety resources, University policies, and violence reporting requirements help us maintain a safe personal, work and learning environment.

Safety

If you are ill, please do not come to class (or the campus, for that matter). For more information about COVID-19 safety and policy can be found here.


Topics and Schedule

Week 1 | Week 2 | Week 3 | Week 4 | Week 5 | Week 6 | Week 7 | Week 8 | Week 9 | Week 10 | Week 11 | Final project presentations


Week 1: Introduction to human population genetics (Sept 27)

Readings:

Materials:
  • Overheads (27 Sep)

Week 2: Genetic and phenotypic variation (Oct 2, 4)

Readings and video resources:
  • Optional: An introduction to R Studio for beginners
  • Optional: An introduction to R for beginners
  • Optional: An introduction to R programming (series)
  • Optional: Review of conditional statements in R
  • if statement in R
  • else and else if statements in R

Materials:
  • Overheads (2 Oct)
  • Overheads (4 Oct)
  • Intro to R, R code ((4 Oct)
  • Intro to R, body fat data (csv format) (4 Oct)
  • Intro to R, body fat data documentation (4 Oct)
  • Intro to R, estradiol data (csv format) (4 Oct)
  • Intro to R, estradiol data documentation (4 Oct)
  • Problem set 1 distributed (Wednesday)

Week 3: Organization of genetic variation (Oct 9, 11)

Readings:

Materials:
  • Overheads (9 Oct)
  • Overheads (11 Oct)
  • Lab exercise 1 (9 Oct)
  • Lab exercise 2 (9 Oct)
  • Lab exercise 1 (11 Oct)
  • Lab exercise 2 (11 Oct)
  • Problem set 1 due (Wednesday)
  • Problem set 2 distributed (Wednesday)

Week 4: Inbreeding and Mutation (Oct 16, 18)

Readings:

Materials:
  • Overheads (16 Oct)
  • Overheads (18 Oct)
  • Lab exercise 2 (16 Oct)
  • Lab exercise 1 (18 Oct)
  • Lab exercise 2 (18 Oct)
  • Dataset for lab (18 Oct)

Week 5: Random Genetic Drift (Oct 23, 25)

Readings:

Materials:
  • Lab exercise 1 (23 Oct)
  • Lab exercise 2 (23 Oct)
  • Lab exercise 1 (25 Oct)
  • Lab exercise 2 (25 Oct)
  • Lab exercise 3 (25 Oct)
  • Problem set 3 distributed (Wednesday)

Week 6: More Drift (Oct 30, Nov 1)

Readings:

Materials:
  • Overheads (01 Nov)
  • Lab exercise 1 (30 Oct)
  • Lab exercise 1 (01 Nov)
  • Problem set 4 distributed (Friday)

Week 7: Natural Selection (Nov 6, 8)

Readings:

Materials:
  • Overheads (6 Nov)
  • Likelihood handout (6 Nov)
  • Code for Rh example (8 Nov)
  • Code for ABO example (8 Nov)

Week 8: Natural Selection in Human Populations (Nov 13, 15)

Readings:

Materials:
  • Overheads (15 Nov)
  • Code from slides (15 Nov)
  • Code output (15 Nov)
  • Problem set 4 distributed (Wednesday)

Week 9: Gene Flow (Nov 20, 22)

Readings:

Materials:
  • Overheads (20 Nov)
  • Two-sex simulation (20 Nov)

Week 10: Human Population Structure and History (Nov 27, 29)

Readings:

Materials:
  • Overheads (27 Nov)
  • Overheads (29 Nov)
  • ape distance matrix for lab (29 Nov)
  • Two-sex 2-allele simulation (27 Nov)
  • Problem set 4 due (Monday)
  • Problem set 5 distributed (Monday)

Week 11: More Human Population Genetics and Genome Evolution (Dec 4, 6)

Readings:

Materials:
  • Overheads (4 Dec)
  • Presentation handout (4 Dec)
  • Wainscoat (1986) data (4 Dec)
  • Wainscoat analysis (4 Dec)
  • Problem set 5 due (Wednesday)

Final Project Presentations: 2:30pm-4:20pm, Wednesday, Dec 13, via Zoom.


  • Course information
    • Scope
    • Times
    • Readings
    • Grading
      • Problems
      • Project
      • Exams
  • Course policies
    • Academic misconduct
    • Accomodation
    • Inclusion
    • Safety
  • Topics & Schedule
    • Week 1
    • Week 2
    • Week 3
    • Week 4
    • Week 5
    • Week 6
    • Week 7
    • Week 8
    • Week 9
    • Week 10
    • Week 11
    • Final
    • Syllabus
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