Resolving fine scale variation from microbial metagenomes

The direct sequencing of DNA from the environment, metagenomics, has transformed microbial ecology. Providing access to the genomic content of hitherto unculturable organisms. Statistical challenges still remain in interpreting this data, however. The most important is probably the high resolution assembly of microbial strains direct from short read metagenome sequences. This will form the terminal aim of this studentship. We will build towards this goal by beginning with the creation of suitable in silico data sets to test approaches. Followed by the tackling of the simpler problem of resolving variants that are present in amplicon data. Finally, we will integrate existing approaches that use co-occurrence across samples to resolve variants on contigs directly into metagenome assemblers. To achieve these aims we will exploit a variety of statistical methods including Bayesian non-parametrics and variational approximations.