Statistical and computational methods for modelling pathogen genetic variation (360G-Wellcome-102426_Z_13_Z)

Bacterial and parasitic genomes exhibit high levels of both diversity and structural variation which make analysis extremely challenging. We focus on P.falciparum, where the standard analysis approach of mapping reads to a reference genome leads to poor characterisations of regions with high sequencediversity or deeply diverged lineages, such as several medically important surface antigen genes. Furthermore, mixed infections are a fundamental part ofmalaria biology, and in order to build good models and ask appropriate population genetic questions, we want to be able to incorporate this. The goalof this D.Phil is to develop data structures that represents all known geneticvariation in the species in a way that preserves coordinates, and then associated statistical methods, to use all the information available about alternative haplotypes when assembling novel genomes. Concretely, as part of the MalariaGEN consortium Pf3k project to sequence 3000 P. falciparum samples and make them publicly available, we will build a population reference graph that combines heterogeneous data, including multiple reference sequences and thousands of unassembled samples. This will allow us to address many questions, such as relating to the biology of surface antigen genes, and use these graphs in association studies.