Measuring the overlap between the var gene repertoires of two P. falciparum parasites is, in principle, easy. Each parasite genome contains a repertoire of approximately 60 var genes, so upon fully sequencing both parasites’ genomes, the number of shared var sequences can be directly counted. In practice, however, only a fraction of each parasite’s var repertoire is likely to be sampled due to the difficulties of whole-genome sequencing for var genes and the stochastic sample provided by PCR techniques. Although a method exists for quantifying repertoire overlap under these subsampled conditions, its bias is well documented and the uncertainty of its estimates cannot be quantified. Here we derive and validate a method to rigorously estimate the repertoire overlap between two parasites from the overlap of their subsampled repertoires. By solving a Bayesian inference problem, this method takes into account the rates of subsampling and produces unbiased and Bayes-optimal estimates of overlap. In addition, it provides a natural framework for computing the uncertainty of its estimates, and can be used in laboratory planning by quantifying the tradeoff between sequencing effort and uncertainty.
Genome sequencing of chimpanzee malaria parasites reveals possible pathways of adaptation to human hosts