ArticleAmerican journal of human genetics2000
Multilocus linkage tests based on affected relative pairs.
Article in American journal of human genetics, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- The missing heritability in type 1 diabetes.Diabetes, obesity & metabolism · 2022Review
- Review
- Linkage analysis in the next-generation sequencing era.Human heredity · 2011Review
- Incorporation of covariates in simultaneous localization of two linked loci using affected relative pairs.BMC genetics · 2010Article
- Expression profiling of human genetic and protein interaction networks in type 1 diabetes.PloS one · 2009Article
- Detecting gene-gene interactions that underlie human diseases.Nature reviews. Genetics · 2009Review
- Conditional tests for localizing trait genes.Human heredity · 2009Article
- Design considerations in a sib-pair study of linkage for susceptibility loci in cancer.BMC medical genetics · 2008Article
- Searching for epistasis and linkage heterogeneity by correlations of pedigree-specific linkage scores.Genetic epidemiology · 2008Article
- A genome-wide scan for type 1 diabetes susceptibility genes in nuclear families with multiple affected siblings in Finland.BMC genetics · 2007Article
- Integrative analysis for finding genes and networks involved in diabetes and other complex diseases.Genome biology · 2007Article
- Exploiting gene x gene interaction in linkage analysis.BMC proceedings · 2007Article
- Powerful multilocus tests of genetic association in the presence of gene-gene and gene-environment interactions.American journal of human genetics · 2006Article
- Searching for epistatic interactions in nuclear families using conditional linkage analysis.BMC genetics · 2005Article
- Linkage to the FOXC2 region of chromosome 16 for varicose veins in otherwise healthy, unselected sibling pairs.Journal of medical genetics · 2005Article
- Multilocus linkage analysis of affected sib pairs.Human heredity · 2005Article
- Search for haplotype interactions that influence susceptibility to type 1 diabetes, through use of unphased genotype data.American journal of human genetics · 2003Article
- Affected-sib-pair data can be used to distinguish two-locus heterogeneity from two-locus epistasis.American journal of human genetics · 2003Article
- Searching for osteoporosis genes in the post-genome era: progress and challenges.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2003Review
- A note on the calculation of empirical P values from Monte Carlo procedures.American journal of human genetics · 2002Article
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Authors and funding
4 authors.
Funding
Abstract
For complex diseases, recent interest has focused on methods that take into account joint effects at interacting loci. Conditioning on effects of disease loci at known locations can lead to increased power to detect effects at other loci. Moreover, use of joint models allows investigation of the etiologic mechanisms that may be involved in the disease. Here we present a method for simultaneous analysis of the joint genetic effects at several loci that uses affected relative pairs. The method is a generalization of the two-locus LOD-score analysis for affected sib pairs proposed by Cordell et al. We derive expressions for the relative risk, lambdaR, to a relative of an affected individual, in terms of the additive and epistatic components of variance at an arbitrary number of disease loci, and we show how these can be used to fit a likelihood model to the identity-by-descent sharing among pairs of affected relatives in extended pedigrees. We implement the method by use of a stepwise strategy in which, given evidence of linkage to disease at m-1 locations on the genome, we calculate the conditional likelihood curve across the genome for an mth disease locus, using multipoint methods similar to those proposed by Kruglyak et al. We evaluate the properties of our method by use of simulated data and present an application to real data from families with insulin-dependent diabetes mellitus.
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