Algorithms towards haplotype-sharing based association studies of case-control traits on pedigree data
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Abstract
Association studies that attempt to link genes with traits are expected to unearth various genomic roots for various diseases. Recently, haplotype based association studies have become popular due to the inheritance information innate to haplotypes. In this work, we provide a summary of recent works that focus on haplotyping and those focusing on association studies. We show that haplotyping is a very promising technique for case−control association studies on pedigree data. We also present a novel haplotyping algorithm that relaxes the assumption of many previous rule based algorithms. We extend the algorithm to compute and enumerate all possible identity-by-state and identity-by-descent sharings. The algorithm is also able to calculate LOD scores, a metric to measure linkage, for every chromosomal region that is free of breakpoints. Our algorithm is implemented in iBDD, which we believe will be highly useful in downstream case−control association studies on pedigree data.