syllabus.md

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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