| Call Number | 15639 |
|---|---|
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | Iuliana Ionita-Laza |
| Type | LECTURE |
| Method of Instruction | In-Person |
| Course Description | This course introduces students to advanced computational and statistical methods used in the design and analysis of high-dimensional genetic data, an area of critical importance in the current era of BIG DATA. The course starts with a brief background in genetics, followed by in depth discussion of topics in genome-wide linkage and association studies, and next-generation sequencing studies. Additional topics such as network genetics will also be covered. Examples from recent and ongoing applications to complex traits will be used to illustrate methods and concepts. Students are required to read relevant papers as assigned by the instructor, and each student is required to present a paper during class. Students are also required to work on a project related to the course material, with midterm evaluation of the progress. We will use one main textbook: The fundamentals of Modern Statistical Genetics by Laird and Lange (Springer, 2012). For further reading, an excellent book is also Handbook of Statistical Genetics, Volume 1 (Wiley, 2007). Another good book is Mathematical and Statistical Methods for Genetic Analysis by Ken Lange (Springer 2002). |
| Web Site | Vergil |
| Department | Biostatistics |
| Enrollment | 0 students (20 max) as of 9:05AM Saturday, December 21, 2024 |
| Subject | Biostatistics |
| Number | P8119 |
| Section | 001 |
| Division | School of Public Health |
| Open To | GSAS, Public Health |
| Section key | 20243BIST8119P001 |