Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis - PubMed (original) (raw)

Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis

Yurii S Aulchenko et al. Genetics. 2007 Sep.

Abstract

For pedigree-based quantitative trait loci (QTL) association analysis, a range of methods utilizing within-family variation such as transmission-disequilibrium test (TDT)-based methods have been developed. In scenarios where stratification is not a concern, methods exploiting between-family variation in addition to within-family variation, such as the measured genotype (MG) approach, have greater power. Application of MG methods can be computationally demanding (especially for large pedigrees), making genomewide scans practically infeasible. Here we suggest a novel approach for genomewide pedigree-based quantitative trait loci (QTL) association analysis: genomewide rapid association using mixed model and regression (GRAMMAR). The method first obtains residuals adjusted for family effects and subsequently analyzes the association between these residuals and genetic polymorphisms using rapid least-squares methods. At the final step, the selected polymorphisms may be followed up with the full measured genotype (MG) analysis. In a simulation study, we compared type 1 error, power, and operational characteristics of the proposed method with those of MG and TDT-based approaches. For moderately heritable (30%) traits in human pedigrees the power of the GRAMMAR and the MG approaches is similar and is much higher than that of TDT-based approaches. When using tabulated thresholds, the proposed method is less powerful than MG for very high heritabilities and pedigrees including large sibships like those observed in livestock pedigrees. However, there is little or no difference in empirical power of MG and the proposed method. In any scenario, GRAMMAR is much faster than MG and enables rapid analysis of hundreds of thousands of markers.

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Figures

F<sc>igure</sc> 1.—

Figure 1.—

Scatterplot of the χ2-statistics coming from the measured-genotype (MG) approach vs. χ2-statistics coming from GRAMMAR, QTDT, and FBAT. The model assumes heritability of 0.28 and a QTL explaining 0.02 of the total variance. Results of analysis of data from 337 sib-trios (A) and ERF pedigree (B) are presented. The dotted line represents a slope of unity.

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References

    1. Abecasis, G. R., L. R. Cardon and W. O. Cookson, 2000. A general test of association for quantitative traits in nuclear families. Am. J. Hum. Genet. 66: 279–292. - PMC - PubMed
    1. Aulchenko, Y. S., S. Ripke, A. Isaacs and C. M. van Duijn, 2007. GenABEL: an R library for genome-wide association analysis. Bioinformatics (in press). - PubMed
    1. Blangero, J., 2004. Localization and identification of human quantitative trait loci: king harvest has surely come. Curr. Opin. Genet. Dev. 14: 233–240. - PubMed
    1. Boerwinkle, E., R. Chakraborty and C. F. Sing, 1986. The use of measured genotype information in the analysis of quantitative phenotypes in man. I. Models and analytical methods. Ann. Hum. Genet. 50(Pt. 2): 181–194. - PubMed
    1. Bourgain, C., and E. Genin, 2005. Complex trait mapping in isolated populations: Are specific statistical methods required? Eur. J. Hum. Genet. 13: 698–706. - PubMed

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