[1][2][3] Phylodynamic analysis includes analyzing genetic diversity, natural selection, and population dynamics of infectious disease pathogen phylogenies during pandemics and studying intra-host evolution of viruses.
The field of bacterial phylodynamics has increased substantially due to the advancement of next-generation sequencing and the amount of data available.
[4] A BLAST search is frequently executed to find similar strains of the pathogen of interest.
There are several way to check for phylogenetic signal in an alignment, such as likelihood mapping, transition/transversions versus divergence plots, and the Xia test for saturation.
Most algorithms used for phylogenetic analysis do not take into recombination into account, which can alter the molecular clock and coalescent estimates of a multiple sequence alignment.
[4] The best fitting nucleotide or amino acid substitution model for a multiple sequence alignment is the first step in phylodynamic analysis.
[4] Testing the reliability of the tree after inferring its phylogeny, is a crucial step in the phylodynamic pipeline.
[4] Methods to test the reliability of a tree include bootstrapping, maximum likelihood estimation, and posterior probabilities in Bayesian analysis.
These methods include estimating the data set's molecular clock, demographic history, population structure, gene flow, and selection analysis.
[4] Phylodynamic results of a data set can also influence better study designs in future experiments.
[5] Typically high quality single-nucleotide polymorphisms (hqSNP) from whole genome V. cholerae sequences are used for phylodynamic analysis.