Recent genome-wide association studies have revealed associations
between many genetic variants and complex conditions. Using
related individuals in these studies has been shown to enhance their
power, as well as to avoid spurious results due to confounding effects. In
particular, pedigree analysis can provide higher power for detecting rare
variants than an association study involving unrelated individuals.

A key ingredient in association studies is imputation and inference of
haplotypes from genotype data. When related individuals are considered,
current haplotype inference methods do not scale to whole-genome
datasets, and their accuracy is limited when considering complex pedigrees
with several founding lineages. In this paper, we present algorithms
for efficient haplotype inference and imputation. Our method,
PhyloPed, leverages the perfect phylogeny model, resulting in an efficient
method with high accuracy. In addition, PhyloPed effectively combines
the founder haplotype information from different lineages and is immune
to inaccuracies in prior information about the founders.