𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Variance-components methods for linkage and association analysis of ordinal traits in general pedigrees

✍ Scribed by G. Diao; D. Y. Lin

Publisher
John Wiley and Sons
Year
2009
Tongue
English
Weight
110 KB
Volume
34
Category
Article
ISSN
0741-0395

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

Many complex human diseases such as alcoholism and cancer are rated on ordinal scales. Well‐developed statistical methods for the genetic mapping of quantitative traits may not be appropriate for ordinal traits. We propose a class of variance‐component models for the joint linkage and association analysis of ordinal traits. The proposed models accommodate arbitrary pedigrees and allow covariates and gene‐environment interactions. We develop efficient likelihood‐based inference procedures under the proposed models. The maximum likelihood estimators are approximately unbiased, normally distributed, and statistically efficient. Extensive simulation studies demonstrate that the proposed methods perform well in practical situations. An application to data from the Collaborative Study on the Genetics of Alcoholism is provided. Genet. Epidemiol. 34: 232–237, 2010.  © 2009 Wiley‐Liss, Inc.

📜 SIMILAR VOLUMES

Semiparametric variance-component models
Semiparametric variance-component models for linkage and association analyses of censored trait data
✍ G. Diao; D.Y. Lin 📂 Article 📅 2006 🏛 John Wiley and Sons 🌐 English ⚖ 203 KB 👁 1 views

## Abstract Variance‐component (VC) models are widely used for linkage and association mapping of quantitative trait loci in general human pedigrees. Traditional VC methods assume that the trait values within a family follow a multivariate normal distribution and are fully observed. These assumptio

Power and robustness of linkage tests fo
Power and robustness of linkage tests for quantitative traits in general pedigrees
✍ Wei-Min Chen; Karl W. Broman; Kung-Yee Liang 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 161 KB 👁 2 views

There are numerous statistical methods for quantitative trait linkage analysis in human studies. An ideal such method would have high power to detect genetic loci contributing to the trait, would be robust to non-normality in the phenotype distribution, would be appropriate for general pedigrees, wo

Quantitative trait linkage analysis by g
Quantitative trait linkage analysis by generalized estimating equations: Unification of variance components and Haseman-Elston regression
✍ Wei-Min Chen; Karl W. Broman; Kung-Yee Liang 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 129 KB 👁 1 views

## Abstract Two of the major approaches for linkage analysis with quantitative traits in humans include variance components and Haseman‐Elston regression. Previously, these were viewed as quite separate methods. We describe a general model, fit by use of generalized estimating equations (GEE), for

MCMC-based linkage analysis for complex
MCMC-based linkage analysis for complex traits on general pedigrees: multipoint analysis with a two-locus model and a polygenic component
✍ Yun Ju Sung; Elizabeth A. Thompson; Ellen M. Wijsman 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 283 KB 👁 1 views

## Abstract We describe a new program lm\_twoqtl, part of the MORGAN package, for parametric linkage analysis with a quantitative trait locus (QTL) model having one or two QTLs and a polygenic component, which models additional familial correlation from other unlinked QTLs. The program has no restr

Comparison of variance components and si
Comparison of variance components and sibpair-based approaches to quantitative trait linkage analysis in unselected samples
✍ Jeff T. Williams; John Blangero 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 128 KB 👁 2 views

We compared the statistical performance of sibpair-based and variance components approaches to multipoint linkage analysis of a quantitative trait in unselected samples. As a benchmark dataset, we used the simulated family data from Genetic Analysis Workshop 10 [Goldin et al., 1997], and each method