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Combining information from linkage and association mapping for next-generation sequencing longitudinal family data.


ABSTRACT: In this analysis, we investigate the contributions that linkage-based methods, such as identical-by-descent mapping, can make to association mapping to identify rare variants in next-generation sequencing data. First, we identify regions in which cases share more segments identical-by-descent around a putative causal variant than do controls. Second, we use a two-stage mixed-effect model approach to summarize the single-nucleotide polymorphism data within each region and include them as covariates in the model for the phenotype. We assess the impact of linkage disequilibrium in determining identical-by-descent states between individuals by using markers with and without linkage disequilibrium for the first part and the impact of imputation in testing for association by using imputed genome-wide association studies or raw sequence markers for the second part. We apply the method to next-generation sequencing longitudinal family data from Genetic Association Workshop 18 and identify a significant region at chromosome 3: 40249244-41025167 (p-value = 2.3 × 10(-3)).

SUBMITTER: Balliu B 

PROVIDER: S-EPMC4143620 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Combining information from linkage and association mapping for next-generation sequencing longitudinal family data.

Balliu Brunilda B   Uh Hae-Won HW   Tsonaka Roula R   Boehringer Stefan S   Helmer Quinta Q   Houwing-Duistermaat Jeanine J JJ  

BMC proceedings 20140617 Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo


In this analysis, we investigate the contributions that linkage-based methods, such as identical-by-descent mapping, can make to association mapping to identify rare variants in next-generation sequencing data. First, we identify regions in which cases share more segments identical-by-descent around a putative causal variant than do controls. Second, we use a two-stage mixed-effect model approach to summarize the single-nucleotide polymorphism data within each region and include them as covariat  ...[more]

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