Postassociation cleaning using linkage disequilibrium information

2010 ◽  
Vol 35 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Buhm Han ◽  
Brian M. Hackel ◽  
Eleazar Eskin
Keyword(s):  
Linkage Disequilibrium ◽  
Linkage Disequilibrium Information

The use of linkage disequilibrium to map quantitative trait loci

2005 ◽  
Vol 45 (8) ◽  
pp. 837 ◽  
Author(s):  
M. E. Goddard ◽  
T. H. E. Meuwissen
Keyword(s):  
Linkage Disequilibrium ◽  
Quantitative Trait Loci ◽  
Statistical Model ◽  
Quantitative Trait ◽  
Linear Models ◽  
Chromosome Segment ◽  
Identical By Descent ◽  
Trait Loci ◽  
Linkage Disequilibrium Information ◽  
Chromosome Segments

This paper reviews the causes of linkage disequilibrium and its use in mapping quantitative trait loci. The many causes of linkage disequilibrium can be understood as due to similarity in the coalescence tree of different loci. Consideration of the way this comes about allows us to divide linkage disequilibrium into 2 types: linkage disequilibrium between any 2 loci, even if they are unlinked, caused by variation in the relatedness of pairs of animals; and linkage disequilibrium due to the inheritance of chromosome segments that are identical by descent from a common ancestor. The extent of linkage disequilibrium due to the latter cause can be logically measured by the chromosome segment homozygosity which is the probability that chromosome segments taken at random from the population are identical by descent. This latter cause of linkage disequilibrium allows us to map quantitative trait loci to chromosome regions. The former cause of linkage disequilibrium can cause artefactual quantitative trait loci at any position in the genome. These artefacts can be avoided by fitting the relatedness of animals in the statistical model used to map quantitative trait loci. In the future it may be convenient to estimate this degree of relatedness between individuals from markers covering the whole genome. The statistical model for mapping quantitative trait loci also requires us to estimate the probability that 2 animals share quantitative trait loci alleles at a particular position because they have inherited a chromosome segment containing the quantitative trait loci identical by descent. Current methods to do this all involve approximations. Methods based on concepts of coalescence and chromosome segment homozygosity are useful, but improvements are needed for practical analysis of large datasets. Once these probabilities are estimated they can be used in flexible linear models that conveniently combine linkage and linkage disequilibrium information.

scholarly journals Reporting Correct p Values in VEGAS Analyses

2017 ◽  
Vol 20 (3) ◽  
pp. 257-259 ◽  
Author(s):  
Julian Hecker ◽  
Anna Maaser ◽  
Dmitry Prokopenko ◽  
Heide Loehlein Fier ◽  
Christoph Lange
Keyword(s):  
Linkage Disequilibrium ◽  
False Positive ◽  
Real Data ◽  
Summary Statistics ◽  
Methodological Framework ◽  
Test Statistics ◽  
P Values ◽  
Different Types ◽  
Linkage Disequilibrium Information ◽  
User Friendly

VEGAS (versatile gene-based association study) is a popular methodological framework to perform gene-based tests based on summary statistics from single-variant analyses. The approach incorporates linkage disequilibrium information from reference panels to account for the correlation of test statistics. The gene-based test can utilize three different types of tests. In 2015, the improved framework VEGAS2, using more detailed reference panels, was published. Both versions provide user-friendly web- and offline-based tools for the analysis. However, the implementation of the popular top-percentage test is erroneous in both versions. The p values provided by VEGAS2 are deflated/anti-conservative. Based on real data examples, we demonstrate that this can increase substantially the rate of false-positive findings and can lead to inconsistencies between different test options. We also provide code that allows the user of VEGAS to compute correct p values.

scholarly journals Combining functional and linkage disequilibrium information in the selection of tag SNPs

2006 ◽  
Vol 23 (1) ◽  
pp. 129-131 ◽  
Author(s):  
P. C. Sham ◽  
S. I. Ao ◽  
J. S. H. Kwan ◽  
P. Kao ◽  
F. Cheung ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Tag Snps ◽  
Linkage Disequilibrium Information ◽  
Selection Of

scholarly journals Gene-based interaction analysis by incorporating external linkage disequilibrium information

2010 ◽  
Vol 19 (2) ◽  
pp. 164-172 ◽  
Author(s):  
Jing He ◽  
Kai Wang ◽  
Andrew C Edmondson ◽  
Daniel J Rader ◽  
Chun Li ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Interaction Analysis ◽  
Linkage Disequilibrium Information

scholarly journals Fine Mapping of Complex Trait Genes Combining Pedigree and Linkage Disequilibrium Information: A Bayesian Unified Framework

Genetics ◽  
2003 ◽  
Vol 163 (4) ◽  
pp. 1497-1510 ◽  
Author(s):  
Miguel Pérez-Enciso
Keyword(s):  
Linkage Disequilibrium ◽  
Fixed Effects ◽  
Simulated Data ◽  
Complex Trait ◽  
Pedigree Information ◽  
Unified Framework ◽  
Linkage Disequilibrium Information ◽  
Sib Families ◽  
Trait Locus ◽  
Better Than

Abstract We present a Bayesian method that combines linkage and linkage disequilibrium (LDL) information for quantitative trait locus (QTL) mapping. This method uses jointly all marker information (haplotypes) and all available pedigree information; i.e., it is not restricted to any specific experimental design and it is not required that phases are known. Infinitesimal genetic effects or environmental noise (“fixed”) effects can equally be fitted. A diallelic QTL is assumed and both additive and dominant effects can be estimated. We have implemented a combined Gibbs/Metropolis-Hastings sampling to obtain the marginal posterior distributions of the parameters of interest. We have also implemented a Bayesian variant of usual disequilibrium measures like D′ and r2 between QTL and markers. We illustrate the method with simulated data in “simple” (two-generation full-sib families) and “complex” (four-generation) pedigrees. We compared the estimates with and without using linkage disequilibrium information. In general, using LDL resulted in estimates of QTL position that were much better than linkage-only estimates when there was complete disequilibrium between the mutant QTL allele and the marker. This advantage, however, decreased when the association was only partial. In all cases, additive and dominant effects were estimated accurately either with or without disequilibrium information.

scholarly journals A comparison between methods for linkage disequilibrium fine mapping of quantitative trait loci

2004 ◽  
Vol 83 (1) ◽  
pp. 41-47 ◽  
Author(s):  
JIHAD M. ABDALLAH ◽  
BRIGITTE MANGIN ◽  
BRUNO GOFFINET ◽  
CHRISTINE CIERCO-AYROLLES ◽  
MIGUEL PÉREZ-ENCISO
Keyword(s):  
Linkage Disequilibrium ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Simulated Data ◽  
Likelihood Method ◽  
Trait Loci ◽  
Single Marker ◽  
Linkage Disequilibrium Information ◽  
Marker Regression ◽  
Trait Locus

We present a maximum likelihood method for mapping quantitative trait loci that uses linkage disequilibrium information from single and multiple markers. We made paired comparisons between analyses using a single marker, two markers and six markers. We also compared the method to single marker regression analysis under several scenarios using simulated data. In general, our method outperformed regression (smaller mean square error and confidence intervals of location estimate) for quantitative trait loci with dominance effects. In addition, the method provides estimates of the frequency and additive and dominance effects of the quantitative trait locus.

scholarly journals Fine Mapping of a Quantitative Trait Locus for Twinning Rate Using Combined Linkage and Linkage Disequilibrium Mapping

Genetics ◽  
2002 ◽  
Vol 161 (1) ◽  
pp. 373-379 ◽  
Author(s):  
Theo H E Meuwissen ◽  
Astrid Karlsen ◽  
Sigbjørn Lien ◽  
Ingrid Olsaker ◽  
Mike E Goddard
Keyword(s):  
Quantitative Trait Locus ◽  
Linkage Disequilibrium ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Middle Part ◽  
Linkage Disequilibrium Mapping ◽  
Chromosome 5 ◽  
Linkage Information ◽  
Linkage Disequilibrium Information ◽  
Trait Locus

Abstract A novel and robust method for the fine-scale mapping of genes affecting complex traits, which combines linkage and linkage-disequilibrium information, is proposed. Linkage information refers to recombinations within the marker-genotyped generations and linkage disequilibrium to historical recombinations before genotyping started. The identity-by-descent (IBD) probabilities at the quantitative trait locus (QTL) between first generation haplotypes were obtained from the similarity of the marker alleles surrounding the QTL, whereas IBD probabilities at the QTL between later generation haplotypes were obtained by using the markers to trace the inheritance of the QTL. The variance explained by the QTL is estimated by residual maximum likelihood using the correlation structure defined by the IBD probabilities. Unlinked background genes were accounted for by fitting a polygenic variance component. The method was used to fine map a QTL for twinning rate in cattle, previously mapped on chromosome 5 by linkage analysis. The data consisted of large half-sib families, but the method could also handle more complex pedigrees. The likelihood of the putative QTL was very small along most of the chromosome, except for a sharp likelihood peak in the ninth marker bracket, which positioned the QTL within a region <1 cM in the middle part of bovine chromosome 5. The method was expected to be robust against multiple genes affecting the trait, multiple mutations at the QTL, and relatively low marker density.

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