Literature DB >> 10597431

An empirical test of the significance of an observed quantitative trait locus effect that preserves additive genetic variation.

S J Iturria1, J T Williams, L Almasy, T D Dyer, J Blangero.   

Abstract

We propose a constrained permutation test that assesses the significance of an observed quantitative trait locus effect against a background of genetic and environmental variation. Permutations of phenotypes are not selected at random, but rather are chosen in a manner that attempts to maintain the additive genetic variability in phenotypes. Such a constraint maintains the nonindependence among observations under the null hypothesis of no linkage. The empirical distribution of the lod scores calculated using permuted phenotypes is compared to that obtained using phenotypes simulated from the assumed underlying multivariate normal model. We make comparisons of univariate analyses for both a quantitative phenotype that appears consistent with a multivariate normal model and a quantitative phenotype containing pronounced outliers. An example of a bivariate analysis is also presented.

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Year:  1999        PMID: 10597431     DOI: 10.1002/gepi.1370170729

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  10 in total

1.  Joint multipoint linkage analysis of multivariate qualitative and quantitative traits. I. Likelihood formulation and simulation results.

Authors:  J T Williams; P Van Eerdewegh; L Almasy; J Blangero
Journal:  Am J Hum Genet       Date:  1999-10       Impact factor: 11.025

Review 2.  From mouse to human: fine mapping of quantitative trait loci in a model organism.

Authors:  M S McPeek
Journal:  Proc Natl Acad Sci U S A       Date:  2000-11-07       Impact factor: 11.205

3.  Quantitative-trait homozygosity and association mapping and empirical genomewide significance in large, complex pedigrees: fasting serum-insulin level in the Hutterites.

Authors:  Mark Abney; Carole Ober; Mary Sara McPeek
Journal:  Am J Hum Genet       Date:  2002-03-04       Impact factor: 11.025

Review 4.  Mapping quantitative trait loci in humans: achievements and limitations.

Authors:  Partha P Majumder; Saurabh Ghosh
Journal:  J Clin Invest       Date:  2005-06       Impact factor: 14.808

5.  Efficient calculation of empirical P-values for genome-wide linkage analysis through weighted permutation.

Authors:  Sarah E Medland; James E Schmitt; Bradley T Webb; Po-Hsiu Kuo; Michael C Neale
Journal:  Behav Genet       Date:  2008-09-23       Impact factor: 2.805

6.  Association testing of the mitochondrial genome using pedigree data.

Authors:  Chunyu Liu; Josée Dupuis; Martin G Larson; Daniel Levy
Journal:  Genet Epidemiol       Date:  2013-01-14       Impact factor: 2.135

7.  Variance components linkage analysis for adjusted systolic blood pressure in the Framingham Heart Study.

Authors:  Martyn C Byng; Sheila A Fisher; Cathryn M Lewis; John C Whittaker
Journal:  BMC Genet       Date:  2003-12-31       Impact factor: 2.797

8.  Association of genetic variations and gene expression in a family-based study.

Authors:  Achilleas N Pitsillides; Seung-Hoan Choi; John D Hogan; Jaeyoung Hong; Honghuang Lin
Journal:  BMC Proc       Date:  2016-10-18

9.  Predicting molecular initiating events using chemical target annotations and gene expression.

Authors:  Joseph L Bundy; Richard Judson; Antony J Williams; Chris Grulke; Imran Shah; Logan J Everett
Journal:  BioData Min       Date:  2022-03-04       Impact factor: 2.522

10.  Quantitative trait loci for bone lengths on chromosome 5 using dual energy X-Ray absorptiometry imaging in the Twins UK cohort.

Authors:  Usha Chinappen-Horsley; Glen M Blake; Ignac Fogelman; Bernet Kato; Kourosh R Ahmadi; Tim D Spector
Journal:  PLoS One       Date:  2008-03-12       Impact factor: 3.240

  10 in total

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