Contrasting identity-by-descent estimators, association studies, and linkage analyses using the Framingham Heart Study data

Abstract

We explored the utility of population- and pedigree-based analyses using the Framingham Heart Study genome-wide 50 k single-nucleotide polymorphism marker data provided for Genetic Analysis Workshop 16. Our aims were: 1) to compare identity-by-descent sharing estimates from variable amounts of data; 2) to apply each of these estimates to a case-control association study designed to control for relatedness among samples; and 3) to contrast these results to those obtained using model-based and model-free linkage analysis methods.

Combining information from linkage and association methods

“…Most groups used knowledge of linkage disequilibrium to reduce their marker panel, using either a threshold correlation between neighboring markers [Hendricks et al, 2009; Yoo et al, 2009a] or a regular marker interval of 1 to 10 SNPs/cM [Callegaro et al, 2009; Daw et al, 2009; Gray-McGuire et al, 2009; Marchani et al, 2009]. Most groups limited their analyses to chromosomes with prior association or linkage signals for their phenotype of interest.…”

“…Mendelian inconsistencies were removed from the pedigree files, and monozygotic twins were pooled. There was some confusion about the multiple pedigree files included in the data distribution, and so one group reconstructed the pedigree file using parent-offspring information alone [Marchani et al, 2009]. …”

“…Gray-McGuire et al [2009] estimated p -values for multivariate linkage analyses by simulating the appropriate asymptotic null distributions [Morris et al, 2008]. Marchani et al [2009] performed trait resimulation [Igo and Wijsman, 2008], to provide empirical p -values based on the actual marker data for variance-component linkage analyses. The real data were also used in a conditional inheritance vector test to estimate linkage and to describe the uncertainty in the estimated linkage statistic [Di and Thompson, 2009].…”

“…Because no two groups used the same criteria for testing, a more precise evaluation is not possible here. The most obvious form of replication involved examining multiple subsets of markers, families, or replicates of the simulated data [Daw et al, 2009; Hendricks et al, 2009; Marchani et al, 2009]. Relationships between phenotypes motivated some to compare regions associated with correlated traits or a single phenotype measured at different times [Gray-McGuire et al, 2009; Li et al, 2009].…”

Estimation and Visualization of Identity-by-Descent within Pedigrees Simplifies Interpretation of Complex Trait Analysis

“…It is also possible to use gl_auto and IBDgraph to: (1) force software developed for single-marker analyses to perform multipoint analysis; (2) perform different linkage analyses on identical data using other statistics, trait models [63] , or phenotypes; (3) estimate empirical p values (e.g. for variancecomponents analyses [64] ); and (4) probabilistically phase and infer genotypes within a pedigree [65] . We may also share gl_auto realizations with a collaborator without sharing raw genotype data, which can help keep samples anonymous and unidentifiable.…”