140.686.01
Advanced Methods for Statistical Genetics and Genomics
- Location:
- East Baltimore
- Term:
- 4th term
- Department:
- Biostatistics
- Credits:
- 3 credits
- Academic Year:
- 2021 - 2022
- Instruction Method:
- TBD
- Class Times:
-
- M W, 1:30 - 2:50pm
- Auditors Allowed:
- Yes, with instructor consent
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructors:
- Contact:
- Nilanjan Chatterjee
- Frequency Schedule:
- Every Other Year
- Next Offered:
- 2023 - 2024
- Resources:
- Prerequisite:
Master or PhD level statistical theory classes equivalent to the 140.646-649 series or higher. Similar level statistical theory classes in other department with a quantitative focus are acceptable, but require instructor approval.
- Description:
-
Covers statistical methods and theory underlying advanced analysis of genetic and genomic data to address mechanistic hypotheses and to build models for prediction. Topics include methods for complex association testing, inference on genetic architecture using mixed model techniques, methods for understanding causal mechanisms using Mendelian randomization and integrative genomic analysis and strategies for clinical translation using risk prediction models. Requires making presentations and critiquing published studies that have used advance statistical methods to make new scientific observations.
- Learning Objectives:
-
Upon successfully completing this course, students will be able to:
- use advanced methods for data analysis with an in depth understanding of strength and weakness of different methods
- identify gaps in current literature and conduct PhD level research to develop new methods
- Methods of Assessment:
This course is evaluated as follows:
- 40% Homework
- 20% Presentation of one selected homework
- 40% Presentation of a paper of student’s choice
- Instructor Consent:
No consent required