For Ph.D. Students with an Emphasis in Quantitative Genomics in Epidemiology
The suggested schedule below contains courses that are required for Epidemiology students supported by the training grant in quantitative genomics. This schedule satisfies the epidemiology requirement that all students take 10 credit hours in two minors (here: biostatistics and genetic epidemiology). Students still need to satisfy other requirements for the epidemiology doctoral degree (e.g. they should choose electives so they are prepared for the substantive portion of the screening exam; they should ensure they have 20 credit hours in epidemiology courses; and they should complete EPI205, which is typically taken in the Fall of Year 3, after completion of the written exam).
Fall – Year 1:
- EPI 201 Introduction to Epidemiology: Methods I
- EPI 249 Molecular Biology for Epidemiologists
- BST 201 Intro to Statistical Methods
- EPI 202 Epidemiologic Methods 2: Elements of Epidemiologic Research
- EPI 507 Genetic Epidemiology
- EH 205 Human Physiology
Spring – Year 1:
- EPI 289 Models for Causal Inference
- BST 210 Analysis of Rates & Proportion or BST 213 Applied Regression for Clinical Research
- BST 280 Introductory Genomics and Bioinformatics for Health Research
- EPI 204 Analysis Case-Control & Cohort
- EH 208 Pathophysiology of Human Disease
- BST 316 Quantitative Genomics Lab Rotation (Wet Lab)
Fall – Year 2:
- EPI 207 Advanced Epidemiologic Methods
- BST 227 Introduction to Statistical Genetics
- EPI 247 Epidemiologic Methods Development – Past and Present
- BST 316 Quantitative Genomics Lab Rotation (Dry Lab)
- Electives
Spring – Year 2:
- BST 223 Applied Survival Analysis or BST 226 Applied Longitudinal Analysis
- BST 316 Quantitative Genomics Lab Rotation (Dry Lab)
- Electives
Other Courses Relevant to Quantitative Genomics
Genetic Epidemiology and Epidemiologic Methods
- EPI 293 Analysis of Genetic Association Studies
- EPI 511 Advanced Population and Medical Genetics
- ID 542 Methods for Mediation and Interaction
- EH 298 Environmental Epigenetics
Molecular Biology, Physiology, and Genetics
- GEN 201 Principles of Genetics
- BCMP 200 Molecular Biology
Biostatistics
- BST 235 Advanced Regression and Statistical Learning
- BST 240 Probability Theory and Applications II
- BST 241 Statistical Inference II
- BST 244 Analysis of Failure Time Data
- BST 245 Multivariate and Longitudinal Data Analysis
- BST 249 Bayesian Methods in Biostatistics or STAT 220 Bayesian Data Analysis
Computational Biology and Bioinformatics
- BST 290 Advanced Computational Biology and Bioinformatics
- Biophysics 170 Quantitative Genomics
- Biophysics 205 Computational and Functional Genomics
Data Structures and Programming
- BST 234 Introduction to Data Structures and Algorithms