Infectious disease genomics: from database to phylodynamics

The ongoing SARS-CoV-2 pandemic has seen an unprecedented amount of genome data generated, with over 2 million complete genomes in the GISAID platform. These data have been pivotal to track the evolution of the virus on a global scale and to detect mutations of epidemiological importance, such as those in variants of concern.

Many important biological questions could be addressed with these data. However, there can be issues assessing data quality and suitability. The main limitation in accessing sequence data from public databases is that many genomes have substantial stretches of missing data and are thus not sufficiently reliable to infer mutational events. Others can lack important metadata, such as travel history or vaccination status.

This project has two key aims:

1. Develop a system where one can select thousands of sequences that meet certain criteria for quality control or the presence of metadata that are fit-for-purpose for epidemiological questions
2. Develop tools to specify Bayesian hierarchical models in an intuitive format that will use the above fit-for-purpose data.