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Advanced Methods for Statistical Genetics and Genomics

East Baltimore
4th term
3 credits
Academic Year:
2021 - 2022
Instruction Method:
Class Times:
  • M W,  1:30 - 2:50pm
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor:
Nilanjan Chatterjee
Frequency Schedule:
Every Other Year
Next Offered:
2023 - 2024

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.


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:

  1. use advanced methods for data analysis with an in depth understanding of strength and weakness of different methods
  2. identify gaps in current literature and conduct PhD level research to develop new methods
Methods of Assessment:

This course is evaluated as follows:

  • 50% Two homework assignments
  • 50% Group presentations of papers of students’ choice

Instructor Consent:

No consent required

Special Comments:

There are no required textbooks. A compiled list of recent publications will be made through CoursePlus ( Students can access the web supplement for this course through the CoursePlus system ( You must create an eLearning account to access this CoursePlus website. The “online library” of the course website contains printable handouts for each lecture. Course schedules, announcements, relevant links, and other organizational information are posted regularly on the course website. Lecture handouts will be available via CoursePlus