PT  - JOURNAL ARTICLE
AU  - Yohei Rosen
AU  - Jordan Eizenga
AU  - Benedict Paten
TI  - Modelling haplotypes with respect to reference cohort variation graphs
AID  - 10.1101/101659
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 101659
4099  - http://biorxiv.org/content/early/2017/01/28/101659.short
4100  - http://biorxiv.org/content/early/2017/01/28/101659.full
AB  - Current statistical models of haplotypes are limited to panels of haplotypes whose genetic variation can be represented by arrays of values at linearly ordered bi- or multiallelic loci. These methods cannot model structural variants or variants that nest or overlap. A variation graph is a mathematical structure that can encode arbitrarily complex genetic variation. We present the first haplotype model that operates on a variation graph-embedded population reference cohort. We describe an algorithm to calculate the likelihood that a haplotype arose from this cohort through recombinations and demonstrate time complexity linear in haplotype length and sublinear in population size. We furthermore demonstrate a method of rapidly calculating likelihoods for related haplotypes. We describe mathematical extensions to allow modelling of mutations. This work is an essential step forward for clinical genomics and genetic epidemiology since it is the first haplotype model which can represent all sorts of variation in the population.