The Maximum-Likelihood-Binomial method revisited: a robust approach for model-free linkage analysis of quantitative traits in large sibships

Abstract

Model-free linkage analysis methods, based on identity-by-descent allele sharing, are commonly used for complex trait analysis. The Maximum-Likelihood-Binomial (MLB) approach, which is based on the hypothesis that parental alleles are binomially distributed among affected sibs, is particularly popular. An extension of this method to quantitative traits (QT) has been proposed (MLB-QTL), based on the introduction of a latent binary variable capturing information about the linkage between the QT and the marker. Interestingly, the MLB-QTL method does not require the decomposition of sibships into constituent sibpairs and requires no prior assumption about the distribution of the QT. We propose a new formulation of the MLB method for quantitative traits (nMLB-QTL) that explicitly takes advantage of the independence of paternal and maternal allele transmission under the null hypothesis of no linkage. Simulation studies under H₀ showed that the nMLB-QTL method generated very consistent type I errors. Furthermore, simulations under the alternative hypothesis showed that the nMLB-QTL method was slightly, but systematically more powerful than the MLB-QTL method, whatever the genetic model, residual correlation, ascertainment strategy and sibship size considered. Finally, the power of the nMLB-QTL method is illustrated by a chromosome-wide linkage scan for a quantitative endophenotype of leprosy infection. Overall, the nMLB-QTL method is a robust, powerful, and flexible approach for detecting linkage with quantitative phenotypes, particularly in studies of non Gaussian phenotypes in large sibships.

Identification of a Major Locus, TNF1, That Controls BCG-Triggered Tumor Necrosis Factor Production by Leukocytes in an Area Hyperendemic for Tuberculosis

“…Indeed, the increase in information achieved in multivariate analyses, resulting from the covariance between measures, can substantially boost power of linkage detection compared to univariate analyses [18]. Here, we extended the new MLB-QTL method [27] to multivariate linkage analysis using a 2-step procedure. The analysis strategy is based on a decomposition of the PCs of the phenotypes followed by a combination of the univariate statistics obtained for each PC.…”

“…The test of linkage is a maximum likelihood ratio test (LRT) that compares the likelihoods under the null hypothesis of no linkage (H 0 ) and the alternative hypothesis of linkage (H 1 ). The test statistic is asymptotically distributed as a 50:50 mixture of χ² distribution with 0 and 1 degree of freedom [26,27].…”

“…We performed bivariate quantitative model-free multipoint linkage analysis of TNF response to BCG and BCG plus IFN-γ by means of the new maximum-likelihood-binomial (MLB) method for quantitative traits (nMLB-QTL version 3.0) [26,27] as implemented in an extension of the GENEHUNTER program [28]. The MLB approach considers the sibship as a whole and does not make any assumption about the distribution of the phenotype.…”

Annual Meeting of the International Genetic Epidemiology Society

“…CNV were called using PennCNV on Illumina 610K data. Genetic data were available for 1369 Alzheimer cases [1], 927 Parkinson cases [2], and 1437 shared controls after CNV specific quality control. Fisher exact test was used for assessing association to CNVs, either at the call or gene level.…”

“…Goddard (1) (1) Kaiser Permanente Northwest Abstract presented on behalf of the CERGEN Study Team. Integrated delivery systems with electronic medical records offer unprecedented opportunity within the US to leverage existing infrastructure, health informatics, and specimen resources for broad-based cohorts to support genomic research.…”