Genome-wide linkage analysis in a general population sample using sigma 2A random effects (SSARs) fitted by Gibbs sampling
Related Experiment Video
Updated: Oct 2, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
L J Palmer1, K B Jacobs, K J Scurrah
1Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA.
Abstract:
We used variance components analysis to investigate the underlying determinants of the quantitative phenotypes (Q1-Q5) and their interrelationships in replicate 42 of the Genetic Analysis Workshop 12 simulated general population. Variance components models were fitted using Gibbs sampling in WinBUGS v1.3. Sigma-squared-A-random-effects (SSARs) were estimated for each phenotype, and were used as derived phenotypes in subsequent linkage analyses. Whole-genome, multipoint linkage analyses were based upon a new Haseman-Elston identity-by descent sib-pair method that takes a weighted combination of the trait-sum and trait-difference. The five quantitative traits simulated were closely correlated with each other and with affection status. The whole-genome screen of quantitative traits associated with the simulated complex disease suggested that one or more major loci regulating Q1 localizes to chromosome 2p and that one or more major loci regulating Q5 may localize to chromosome 1p.
Related Concept Videos
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
Single Nucleotide Polymorphisms-SNPs