Special Topics in Genetics: Computational Genetics of Big Data


Spring 2017




Genetics 01:447:380 or Genetic Analysis I 01:447:384

Course Description

The main focus of this course is application of R programming to genetic data. In this course, we will focus specifically on big data, that is, data sets with large numbers of measurements. The primary data sets considered will contain RNA-seq and/or other expression data for multiple/all genes in a given set of individuals.

Students will learn how to acquire such data, manipulate and plot this data for exploratory data analyses in R, and learn statistical analyses to test specific hypotheses. In addition, students will learn how to stimulate data under different hypotheses, and how to perform power and sample size calculations for different statistical methods applied to real or simulated data. 

Course URL

 A Sakai website will be provided 

Course Satisfies Learning Goals

The course satisfies the following Core Curriculum Learning Goals:

  1. Employment of current technologies to access information, to conduct research, and to communicate findings.
  2. Analysis and critical assessment of information from traditional and emergent technologies.

 Exams, Assignments, and Grading Policy

There are three types of assignments in this class: (i) Programming Homework Assignments; (ii) Discussion Forums; and (iii) Quizzes. Also, there will be a final (cumulative) quiz, and a final programming project. All detailed information about each type of assignment will be provided in the syllabus, available the first day of class. Grades will be calculated based on overall course performance. 

Course Materials

This course is almost entirely computer-based, and the course will held in a computer lab. The computer lab has Windows 8 computers. Class materials and files should be copied after each class to a portable USB flash drive (Windows formatted) to continue working at home. No textbook is required as most of the needed material is made available during class or online.

Course Closed?

If this course is closed or you require a special permission number, please add your name to the wait list by using the following link: Wait List Sign Up for Spring 2018 Courses. If you have any questions or concerns, please  contact Kathleen McDonald in the Genetics Undergraduate Office (This email address is being protected from spambots. You need JavaScript enabled to view it.)


Dr. Derek Gordon
Office: Nelson Biological Labs, Room C213
Phone: 848-445-3386
Email:  This email address is being protected from spambots. You need JavaScript enabled to view it. (preferred method of contact)

Dr. Premal Shah
Office: Life Sciences Building, Room 326
Phone: 848-445-9664
Email:  This email address is being protected from spambots. You need JavaScript enabled to view it.

** All information is subject to change at the discretion of the course coordinator.



Registration Information for Spring 2023!

CHECK OUT THE OUGI VIRTUAL FRONT DESK!  Our staff is available via zoom weekdays 9:00 am - 4:30 pm (closed for lunch between 12-1 pm) to answer questions regarding registration for Spring 2023!



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