Abstract
Identifying segments in the genome of different individuals that are identical-by-descent (IBD) is a fundamental element of genetics. IBD data is used for numerous applications including demographic inference, heritability estimation, and mapping disease loci. Simultaneous detection of IBD over multiple haplotypes has proven to be computationally difficult. To overcome this, many state of the art methods estimate the probability of IBD between each pair of haplotypes separately. While computationally efficient, these methods fail to leverage the clique structure of IBD resulting in less powerful IBD identification, especially for small IBD segments.We develop a hybrid approach (PIGS), which combines the computational efficiency of pairwise methods with the power of multiway methods. It leverages the IBD graph structure to compute the probability of IBD conditional on all pairwise estimates simultaneously. We show via extensive simulations and analysis of real data that our method produces a substantial increase in the number of identified small IBD segments.
Highlights
Identity-by-descent (IBD) is a fundamental genetics concept with broad applications to both medical and population genetics [1]
DASH and Efficient Multiple-IBD (EMI) were run in the same way as we described for identifying cliques, the resulting clique edges were converted into IBD calls and merged with the original input
PIGS combines the computational efficiency of pairwise methods with the power advantages of multiway methods
Summary
Identity-by-descent (IBD) is a fundamental genetics concept with broad applications to both medical and population genetics [1]. Two haplotypes are identical-by-state (IBS) if they share the same sequence. Two haplotypes are IBD if they are both IBS and were inherited from a common ancestor [2]. IBD contains information both about sequence similarity and about the historical relationship of individuals. IBD has been used for such applications as detecting cryptic relatedness between individuals [3], estimating components of heritability [4], inferring evolutionary and demographic history [5,6,7], and mapping disease loci [8,9,10,11,12,13]. The identification of IBD segments from genome-wide genotyping studies, and more recently sequencing studies, has important implications for studies of complex human phenotypes
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