layout | title | date | categories | permalink |
---|---|---|---|---|
page |
Syllabus |
2019-09-17 17:11:23 -0400 |
jekyll update |
/syllabus/ |
Lecture: Introduction: Phylogenetic insights into infectious disease dynamics
Lab: Wrangling and aligning sequence data, building ML phylogenies
No class Jan 15th: MLK Day
Lecture/Lab: First a step back: bioinformatic pipelines for next-generation sequencing data
Lecture: The statistical underpinnings of Bayesian and ML inference
Lab: MCMC in BEAST: priors, posteriors, mixing, convergence, ect.
Lecture: Exploring the origins of epidemics with phylogeography
Lab: Discrete trait models for phylogeographic analysis
Lecture: Coalescent theory and the population genetics of molecular evolution
Lab: Bayesian skyline plots in BEAST
Bonus Lab (optional): Structured coalescent models with MASCOT
Lecture: Inferring transmission trees and who’s infecting whom
Side topic: Accounting for within-host diversity
Lab: Transmission tree reconstruction with SCOTTI
Lecture: Non-tree like evolution: Recombination, ancestral recombination graphs and clonal frames
Side topic: Slowly evolving bacteria and fungi
Lab: Detecting recombination in RDP4
Lecture: Recombine often or perish: Genome evolution in bacterial and eukaryotic pathogens
Lab: Organize mini research projects
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
Lecture: Modeling transmission dynamics with SIR models
Lab: SIR model practical; simulating epidemics in Python/Jupyter
Lecture: Modeling and simulating evolution with generative tree models
Lab: How good is BEAST? Simulating trees and sequence data to test our algorithms
Lecture: Putting it all together with phylodynamics: phylogenetics meets epidemic modeling
Lab: Fitting SIR models to phylogenies
Lecture: After the data deluge: scaling strategies for massive genomic datasets
Lab: Tracking SARS-CoV-2 imports using massive genomic datasets
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)
Last day of class: Team presentations