Syllabus
Spring 2024
Week 1: Jan 8 - 12
Lecture: Introduction: Phylogenetic insights into infectious disease dynamics 
Lab: Wrangling and aligning sequence data, building ML phylogenies
Week 2: Jan 15 - 19
No class Jan 15th: MLK Day 
Lecture/Lab: First a step back: bioinformatic pipelines for next-generation sequencing data
Week 3: Jan 22 - 26
Lecture: The statistical underpinnings of Bayesian and ML inference 
 
Lab: MCMC in BEAST: priors, posteriors, mixing, convergence, ect.
Week 4: Jan 29 - Feb 2
Lecture:  Exploring the origins of epidemics with phylogeography 
Lab: Discrete trait models for phylogeographic analysis
Week 5: Feb 5 - 9
Lecture: Coalescent theory and the population genetics of molecular evolution 
Lab: Bayesian skyline plots in BEAST 
Bonus Lab (optional): Structured coalescent models with MASCOT
Week 6: Feb 12 - 16
Lecture: Inferring transmission trees and who’s infecting whom 
Side topic: Accounting for within-host diversity 
Lab: Transmission tree reconstruction with SCOTTI
Week 7: Feb 19 - 23
Lecture: Non-tree like evolution: Recombination, ancestral recombination graphs and clonal frames 
Side topic: Slowly evolving bacteria and fungi 
Lab: Detecting recombination in RDP4
Week 8: Feb 26 - March 1
Lecture: Recombine often or perish: Genome evolution in bacterial and eukaryotic pathogens 
Lab: Organize mini research projects
Week 9: March 4 - 8
Lecture: Multi-type birth-death models and adaptive molecular evolution 
Lab: Estimating the fitness of drug resistance mutations in BDMM
March 11 - 15: SPRING BREAK
Week 10: March 18 - 22
Lecture: Modeling transmission dynamics with SIR models 
Lab: SIR model practical; simulating epidemics in Python/Jupyter
Week 11: March 25 - 29
Lecture: Modeling and simulating evolution with generative tree models 
Lab: How good is BEAST? Simulating trees and sequence data to test our algorithms
Week 12: April 1 - 5
Lecture: Putting it all together with phylodynamics: phylogenetics meets epidemic modeling 
Lab: Fitting SIR models to phylogenies
Week 13: April 8 - 12
Lecture: After the data deluge: scaling strategies for massive genomic datasets 
 
Lab: Tracking SARS-CoV-2 imports using massive genomic datasets
Week 14: April 15 - 19
Lecture: Predicting the (very near) future: Forecasting pathogen evolution 
 
Lab: Discussion of Lusckza and Lassig (Nature, 2015) and Morris et al. (Trends in Micro, 2018)
Week 15: April 22
Last day of class: Team presentations