Literature DB >> 16319490

The bias introduced by population stratification in IBD based linkage analysis.

Tao Wang1, Robert C Elston.   

Abstract

The lack of replication of model-free linkage analyses performed on complex diseases raises questions about the robustness of these methods to various biases. The confounding effect of population stratification on a genetic association study has long been recognized in the genetic epidemiology community. Because the estimation of the number of alleles shared identical by descent (IBD) does not depend on the marker allele frequency when founders of families are observed, model-free linkage analysis is usually thought to be robust to population stratification. However, for common complex diseases, the genotypes of founders are often unobserved and therefore population stratification has the potential to impair model-free linkage analysis. Here, we demonstrate that, when some or all of the founder genotypes are missing, population stratification can introduce deleterious effects on various model-free linkage methods or designs. For an affected sib pair design, it can cause excess false-positive discoveries even when the trait distribution is homogeneous among subpopulations. After incorporating a control group of discordant sib pairs or for a quantitative trait, two circumstances must be met for population stratification to be a confounder: the distributions for both the marker and the trait must be heterogeneous among subpopulations. When this occurs, the bias can result in either a liberal, and hence invalid, test or a conservative test. Bias can be eliminated or alleviated by inclusion of founders' or other family members' genotype data. When this is not possible, new methods need to be developed to be robust to population stratification. Copyright (c) 2005 S. Karger AG, Basel.

Mesh:

Year:  2005        PMID: 16319490     DOI: 10.1159/000089867

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  2 in total

1.  A family-based association test to detect gene-gene interactions in the presence of linkage.

Authors:  Lizzy De Lobel; Lutgarde Thijs; Tatiana Kouznetsova; Jan A Staessen; Kristel Van Steen
Journal:  Eur J Hum Genet       Date:  2012-03-14       Impact factor: 4.246

2.  High-density genomewide linkage analysis of exceptional human longevity identifies multiple novel loci.

Authors:  Steven E Boyden; Louis M Kunkel
Journal:  PLoS One       Date:  2010-08-31       Impact factor: 3.240

  2 in total

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