Comparison of model-free linkage mapping strategies for the study of a complex trait

Amos, Christopher I.; Krushkal, Julia; Thiel, T. J.; Young, Alexander I.; Zhu, Dakai; Boerwinkle, Eric; Andrade, Mariza de

doi:10.1002/(sici)1098-2272(1997)14:6<743::aid-gepi30>3.0.co;2-o

Cited by 44 publications

(26 citation statements)

References 3 publications

(2 reference statements)

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“…4.0, 1999]. Just like the approaches that fit a bivariate distribution to the sib-pair residuals, whether using a likelihood based on normality or a quasilikelihood [Amos, 1994;Amos et al, 1996Amos et al, , 1997Almasy and Blangero, 1998], our model ignores moments higher than the first two in the distribution of the residuals of model (6). Unlike those approaches, on the other hand, by modeling the sibs' covariance directly in a linear regression approach the computation becomes much less intensive.…”

Section: Discussionmentioning

confidence: 99%

“…This ignores the information available in the sib-pair trait sum [Wright, 1997;Gaines and Elston, 1969]. It has also been shown that maximum likelihood using a multivariate normal distribution to model the individual sib values, rather than just the pair differences, leads to appreciably more power [Fulker and Cherny, 1996;Amos et al, 1997] in the case of a continuous trait. Single and Finch [1995] showed that when sibships of size larger than two are analyzed, increased power is obtained when a generalized least squares regression is performed to allow for the correlations between the pairs of squared sib-pair trait differences.…”

Section: Introductionmentioning

confidence: 99%

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Haseman and Elston revisited

et al. 2000

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Haseman and Elston revisited

et al. 2000

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“…We used the Fulker-Cardon approximation for IM, which has been used extensively for the study of linkage in large pedigrees because the exact computation of IBD sharing is not feasible in this context. For smaller families such as those studied here, the Fulker-Cardon approximation loses a small proportion of informativeness (Amos et al 1997) compared with exact calculation using the Lander-Green algorithm (Kruglyak and Lander 1995). For our comparison, computational speed is critical and the slight decrease in information caused by using the Fulker-Cardon approximation should not affect our conclusions.…”

Section: Discussionmentioning

confidence: 99%

An Empirical Bayes Method for Updating Inferences in Analysis of Quantitative Trait Loci Using Information From Related Genome Scans

Zhang

Wiener²,

Beasley

et al. 2006

Genetics

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Individual genome scans for quantitative trait loci (QTL) mapping often suffer from low statistical power and imprecise estimates of QTL location and effect. This lack of precision yields large confidence intervals for QTL location, which are problematic for subsequent fine mapping and positional cloning. In prioritizing areas for follow-up after an initial genome scan and in evaluating the credibility of apparent linkage signals, investigators typically examine the results of other genome scans of the same phenotype and informally update their beliefs about which linkage signals in their scan most merit confidence and follow-up via a subjective-intuitive integration approach. A method that acknowledges the wisdom of this general paradigm but formally borrows information from other scans to increase confidence in objectivity would be a benefit. We developed an empirical Bayes analytic method to integrate information from multiple genome scans. The linkage statistic obtained from a single genome scan study is updated by incorporating statistics from other genome scans as prior information. This technique does not require that all studies have an identical marker map or a common estimated QTL effect. The updated linkage statistic can then be used for the estimation of QTL location and effect. We evaluate the performance of our method by using extensive simulations based on actual marker spacing and allele frequencies from available data. Results indicate that the empirical Bayes method can account for between-study heterogeneity, estimate the QTL location and effect more precisely, and provide narrower confidence intervals than results from any single individual study. We also compared the empirical Bayes method with a method originally developed for meta-analysis (a closely related but distinct purpose). In the face of marked heterogeneity among studies, the empirical Bayes method outperforms the comparator. MOST genome scans for linkage in mapping quantitative trait loci (QTL) are analyzed without formal consideration of information provided by other genome scans of the same QTL. Investigators often evaluate scans other than their own when deciding which regions merit further investigation, but they have limited options for formally integrating the data. Individual genome scans have low power to detect QTL and provide imprecise estimates of their location and effect, especially when the effect is small. As a consequence, follow-up for fine mapping and positional cloning is problematic. When multiple studies of the same QTL have been conducted, an analysis method that can formally integrate data from multiple genome scan studies is emerging as a useful and powerful tool in the field of linkage analysis.Although closely related, the method we offer should not be conflated with meta-analysis. Meta-analysis, which can be viewed as a set of statistical procedures designed to summarize statistics across independent studies that address similar scientific questions, is one way to use data from multiple genome s...

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“…For all traits, skewness and kurtosis were further checked for the residuals in the polygenic models and we did not observe departure from normality after adjustment for covariates. A maximum likelihood approach was then implemented in SOLAR to calculate heritability, proportion of alleles shared identical-by-descent (IBD), and multipoint LOD scores ( 31,32 ). Empirical p-values for LOD scores were computed based on 15,000 replicates in which a fullyinformative marker, unlinked to the specifi c trait, was simulated and used to compute possible LOD scores.…”

Section: Statistical Analysesmentioning

confidence: 99%