Association mapping via a class of haplotype-sharing statistics
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
Andrew S Allen1, Glen A Satten
1Department of Biostatistics and Bioinformatics, Duke University, Hock Plaza, Suite 1102, 2424 Erwin Road, Durham, North Carolina 27705, USA. andrew.s.allen@duke.edu
Abstract:
We present a class of haplotype-sharing statistics useful for association mapping in case-parent trio data. The framework presented allows derivation of novel tests as well as new simplified variance estimators for previously proposed tests. We give an overview of this framework and apply four such tests to the simulated data of Genetic Analysis Workshop 15. We find that these haplotype-based statistics result in greater power and better risk locus localization than the single locus single-nucleotide polymorphism analysis.
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