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An exploration of heterogeneity in genetic analysis of complex pedigrees: linkage and association using whole genome sequencing data in the MAP4 region.


ABSTRACT: We conduct pedigree-based linkage and association analyses of simulated systolic blood pressure data in the nonascertained large Mexican American pedigrees provided by Genetic Analysis Workshop 18, focusing on observed sequence variants in MAP4 on chromosome 3. Because pedigrees are large and sequence data have been completed by imputation, it is feasible to conduct analysis for each pedigree separately as well as for all pedigrees combined. We are interested in quantifying and explaining between-pedigree heterogeneity in linkage and association signals. To this end, we first examine minor allele frequency differences between pedigrees. In some of the pedigrees, rare and low-frequency variants occur at a higher prevalence than in all pedigrees combined. In simulation replicate 1, we conduct variance-components linkage and association analysis of all 894 MAP4 variants to compare analytic approaches in single pedigree and combined analysis. In all 200 replicates, we similarly examine the 15 causal variants in MAP4 known under the generating model. We illustrate how random allele frequency variation among pedigrees leads to heterogeneity in pedigree-specific linkage and association signals.

SUBMITTER: Bull SB 

PROVIDER: S-EPMC4143705 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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An exploration of heterogeneity in genetic analysis of complex pedigrees: linkage and association using whole genome sequencing data in the MAP4 region.

Bull Shelley B SB   Chen Zhijian Z   Tan Kuan-Rui KR   Poirier Julia J  

BMC proceedings 20140617 Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo


We conduct pedigree-based linkage and association analyses of simulated systolic blood pressure data in the nonascertained large Mexican American pedigrees provided by Genetic Analysis Workshop 18, focusing on observed sequence variants in MAP4 on chromosome 3. Because pedigrees are large and sequence data have been completed by imputation, it is feasible to conduct analysis for each pedigree separately as well as for all pedigrees combined. We are interested in quantifying and explaining betwee  ...[more]

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