Ancestral haplotype-based association mapping with generalized linear mixed models accounting for stratification | Zendy

Z. Zhang | Zendy; François Guillaume | Zendy; Arnaud Sartelet | Zendy; Carole Charlier | Zendy; Michel Georges | Zendy; Frédéric Farnir | Zendy; Tom Druet | Zendy

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Ancestral haplotype-based association mapping with generalized linear mixed models accounting for stratification

Author(s) -

Z. Zhang,

François Guillaume,

Arnaud Sartelet,

Carole Charlier,

Michel Georges,

Frédéric Farnir,

Tom Druet

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts348

Subject(s) - population stratification , haplotype , kinship , software , association (psychology) , genetic association , markov chain , computer science , single nucleotide polymorphism , stratification (seeds) , population , data mining , biology , machine learning , genetics , allele , programming language , psychology , demography , gene , law , psychotherapist , sociology , genotype , germination , political science , seed dormancy , botany , dormancy

In many situations, genome-wide association studies are performed in populations presenting stratification. Mixed models including a kinship matrix accounting for genetic relatedness among individuals have been shown to correct for population and/or family structure. Here we extend this methodology to generalized linear mixed models which properly model data under various distributions. In addition we perform association with ancestral haplotypes inferred using a hidden Markov model.

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