Abstract
BackgroundWe address the task of extracting accurate haplotypes from genotype data of individuals of large F1 populations for mapping studies. While methods for inferring parental haplotype assignments on large F1 populations exist in theory, these approaches do not work in practice at high levels of accuracy.ResultsWe have designed iXora (Identifying crossovers and recombining alleles), a robust method for extracting reliable haplotypes of a mapping population, as well as parental haplotypes, that runs in linear time. Each allele in the progeny is assigned not just to a parent, but more precisely to a haplotype inherited from the parent. iXora shows an improvement of at least 15% in accuracy over similar systems in literature. Furthermore, iXora provides an easy-to-use, comprehensive environment for association studies and hypothesis checking in populations of related individuals.ConclusionsiXora provides detailed resolution in parental inheritance, along with the capability of handling very large populations, which allows for accurate haplotype extraction and trait association. iXora is available for non-commercial use from http://researcher.ibm.com/project/3430.
Highlights
We address the task of extracting accurate haplotypes from genotype data of individuals of large F1 populations for mapping studies
Haplotypes are useful for inferring the underlying causal genetic basis of the traits in mapping populations as one can more efficiently evaluate the parental inheritance of the haplotype implicated in the determination of the trait [1,2]. iXora is suited to plant breeding, in which mapping populations of individuals of inbred parents are utilized. iXora uses a novel approach by effectively utilizing the large data size and exploiting the fortuitous combinatorial structure in the problem
Through simulation studies we show an improvement of about 15% accuracy in parental haplotype assignment over the best method
Summary
While methods for inferring parental haplotype assignments on large F1 populations exist in theory, these approaches do not work in practice at high levels of accuracy. We address the task of extracting accurate haplotypes from genotype data of individuals of large F1 populations for mapping studies. IXora is suited to plant (or animal) breeding, in which mapping populations of individuals of inbred (or non-inbred) parents are utilized. IXora uses a novel approach by effectively utilizing the large data size and exploiting the fortuitous combinatorial structure in the problem.
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