RT Journal Article
SR Electronic
T1 Modelling haplotypes with respect to reference cohort variation graphs
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 101659
DO 10.1101/101659
A1 Yohei Rosen
A1 Jordan Eizenga
A1 Benedict Paten
YR 2017
UL http://biorxiv.org/content/early/2017/01/28/101659.abstract
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.