Inferential testing for linkage with GENEHUNTER‐MODSCORE: The impact of the pedigree structure on the null distribution of multipoint MOD scores

Mattheisen, Manuel; Dietter, Johannes; Knapp, Michael; Baur, Max P.; Strauch, Konstantin

doi:10.1002/gepi.20264

Cited by 14 publications

(24 citation statements)

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“…Further, the distribution of the maximized LOD score depends on pedigree size and structure, and it is therefore preferable to perform simulations using the structures of the families from the sample at hand rather than to rely on a generic null distribution [30] . We apply this recommendation in the two-locus setting.…”

Section: Simulation Of the Null Distribution Of Statistics Maximized mentioning

confidence: 99%

“…In arbitrary pedigrees, the theoretical null distribution of onelocus LOD scores maximized over the genetic model is not known and computer simulations must be performed to approximate it [30] . Further, the distribution of the maximized LOD score depends on pedigree size and structure, and it is therefore preferable to perform simulations using the structures of the families from the sample at hand rather than to rely on a generic null distribution [30] .…”

Section: Simulation Of the Null Distribution Of Statistics Maximized mentioning

confidence: 99%

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A New Strategy for Linkage Analysis under Epistasis Taking into Account Genetic Heterogeneity

et al. 2009

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Background/Aims: Epistasis, the biological interaction of multiple genes modulating their individual effects, is likely omnipresent in complex diseases, and modelling epistasis in linkage studies can help detect loci with little marginal effect and detect epistatic effects themselves. We propose a complete three-step strategy for parametric linkage analysis under epistasis and heterogeneity in extended pedigrees. Methods: (1) Loci most likely involved in epistatic interactions are pre-screened using two-locus one-marker analyses. (2) Among selected loci, linkage to each locus is evaluated conditionally on linkage information at another locus under two-locus epistatic models. Linkage statistics are maximized over a space of epistatic models to avoid misspecification of model parameters. (3) Families linked to the conditioning locus are selected to deal with heterogeneity between pairs of epistatically interacting loci and other unlinked loci. Properties of conditional linkage statistics prevent the introduction of bias. Results: Simulations reveal important gains in power to detect a locus with weak marginal effect involved in epistatic interaction. Application of our methods to schizophrenia and bipolar disorder in Eastern Quebec kindreds suggests epistasis between three locus pairs for bipolar disorder: 8p11-16p13, 15q11-16p13 and 18q12-15q11. Conclusion: These results suggest that the proposed strategy is powerful for tackling complex phenotypes involving epistasis and heterogeneity.

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Section: Simulation Of the Null Distribution Of Statistics Maximized mentioning

confidence: 99%

Section: Simulation Of the Null Distribution Of Statistics Maximized mentioning

confidence: 99%

A New Strategy for Linkage Analysis under Epistasis Taking into Account Genetic Heterogeneity

et al. 2009

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“…Fortunately, the previous program extension GENEHUNT-ER-MODSCORE, which calculates MOD scores for dichotomous traits [18] , was already able to perform the p value calculation. The MOD score distribution was simulated by creating pedigrees with the same structure and the same phenotypes as the original data set, randomly generating marker data under the null hypothesis of no linkage.…”

Section: Validationmentioning

confidence: 99%

“…In most cases, and particularly for quantitative phenotypes, the null distribution is unknown and the p value has to be determined empirically. The approach we use to determine p values had already been implemented in GENEHUNTER-MOD-SCORE, which performs MOD score analysis for dichotomous traits (see [18] for a thorough description). The empirical p value is calculated by simulating data sets under the null hypothesis: the original data set is taken, and founder alleles at the marker loci are assigned randomly, taking the corresponding marker allele frequencies into account.…”

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confidence: 99%

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Parameter Estimation and Quantitative Parametric Linkage Analysis with GENEHUNTER-QMOD

Künzel

Strauch²

2012

Hum Hered

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Objective: We present a parametric method for linkage analysis of quantitative phenotypes. The method provides a test for linkage as well as an estimate of different phenotype parameters. We have implemented our new method in the program GENEHUNTER-QMOD and evaluated its properties by performing simulations. Methods: The phenotype is modeled as a normally distributed variable, with a separate distribution for each genotype. Parameter estimates are obtained by maximizing the LOD score over the normal distribution parameters with a gradient-based optimization called PGRAD method. Results: The PGRAD method has lower power to detect linkage than the variance components analysis (VCA) in case of a normal distribution and small pedigrees. However, it outperforms the VCA and Haseman-Elston regression for extended pedigrees, nonrandomly ascertained data and non-normally distributed phenotypes. Here, the higher power even goes along with conservativeness, while the VCA has an inflated type I error. Parameter estimation tends to underestimate residual variances but performs better for expectation values of the phenotype distributions. Conclusion: With GENEHUNTER-QMOD, a powerful new tool is provided to explicitly model quantitative phenotypes in the context of linkage analysis. It is freely available at http://www.helmholtz-muenchen.de/genepi/downloads.

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Genome‐wide linkage scan of nonsyndromic orofacial clefting in 91 families of central European origin

Mangold

Reutter

Birnbaum

et al. 2009

American J of Med Genetics Pt A

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Orofacial clefts are among the most common of all congenital disorders. Nonsyndromic cases of cleft lip with or without cleft palate (NSCL/P) and cleft palate only (NSCPO) are considered to have a multifactorial etiology which involves both genetic and environmental factors. We present the results of a genome-wide linkage scan in 91 families of central European descent with nonsyndromic orofacial clefts (NSC). The sample included 74 NSCL/P families, 15 NSCPO families, and 2 mixed families (a total of 217 affected and 230 unaffected individuals were genotyped). We genotyped 542 microsatellite markers (average intermarker distance = 6.9 cM). Multipoint nonparametric linkage analysis was performed using Allegro 2.0f. In addition to the factors investigated in previous genome-wide linkage analyses, we searched for sex-specific susceptibility loci, loci demonstrating parental imprinting and loci that are shared by NSCL/P and NSCPO. Several genomic regions likely to contain susceptibility loci for NSC were identified at the level of nominal significance. Some of these overlap with regions identified in previous studies. Suggestive evidence of linkage was obtained for the loci 4q21-q26 and 1p31-p21, with the chromosome 1 locus showing a male-specific genetic effect. Our study has identified promising chromosomal regions for the identification of NSC-associated genes, and demonstrates the importance of performing detailed statistical analyses which take into account complex genetic mechanisms such as sex-specific effects and genomic imprinting. Further research in large patient samples is necessary to identify factors common to NSCL/P and NSCPO.

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Inferential testing for linkage with GENEHUNTER‐MODSCORE: The impact of the pedigree structure on the null distribution of multipoint MOD scores

Cited by 14 publications

References 24 publications

A New Strategy for Linkage Analysis under Epistasis Taking into Account Genetic Heterogeneity

A New Strategy for Linkage Analysis under Epistasis Taking into Account Genetic Heterogeneity

Parameter Estimation and Quantitative Parametric Linkage Analysis with GENEHUNTER-QMOD

Genome‐wide linkage scan of nonsyndromic orofacial clefting in 91 families of central European origin

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