SNP Subset Selection for Genetic Association Studies

Byng, M C; Whittaker, John C.; Cuthbert, Andrew; Mathew, Christopher G.; Lewis, Cathryn M.

doi:10.1046/j.1529-8817.2003.00055.x

Cited by 31 publications

(30 citation statements)

References 11 publications

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“…This is due to the fact that the average in the table is taken across all loci rather than across just the "common" loci. Similar tag SNP selection methods have been implemented by many others including Byng et al [2003].…”

Section: Simulation Studymentioning

confidence: 99%

Analysis of multiple SNPs in a candidate gene or region

Chapman

Whittaker

2008

Genetic Epidemiology

136

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We consider the analysis of multiple SNPs within a gene or region. The simplest analysis of such data is based on a series of single SNP hypothesis tests, followed by correction for multiple testing, but it is intuitively plausible that a joint analysis of the SNPs will have higher power, particularly when the causal locus may not have been observed. However, standard tests, such as a likelihood ratio test based on an unrestricted alternative hypothesis, tend to have large numbers of degrees of freedom and hence low power. This has motivated a number of alternative test statistics. Here we compare several of the competing methods, including the multivariate score test (Hotelling's test) of Chapman et al. [2003], Fisher's method for combining p-values, the minimum p-value approach, a Fourier transform based approach recently suggested by Wang and Elston [2007] and a Bayesian score statistic proposed for microarray data by Goeman et al. [2005]. Some relationships between these methods are pointed out, and simulation results given to show that the minimum p-value and the Goeman et al. [2005] approaches work well over a range of scenarios. The Wang and Elston approach often performs poorly; we explain why, and show how its performance can be substantially improved.

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Section: Simulation Studymentioning

confidence: 99%

Analysis of multiple SNPs in a candidate gene or region

Chapman

Whittaker

2008

Genetic Epidemiology

136

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“…Second, the optimal methodology to select a nonredundant tag SNP set at a locus is still evolving. 21,47,48 We tested the performance of our set using several approaches; the tag SNPs we selected captured the majority of common variation at the NOS3 locus. Third, our cohort was middle-aged to elderly and white, potentially limiting generalizability to individuals who are younger or of other ethnicities/races.…”

Section: Study Limitations and Strengthsmentioning

confidence: 99%

Common Genetic Variation at the Endothelial Nitric Oxide Synthase Locus and Relations to Brachial Artery Vasodilator Function in the Community

et al. 2005

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Background-Sequence variants at the endothelial nitric oxide synthase (NOS3) locus have been associated with endothelial function measures, but replication has been limited. Methods and Results-In reference pedigrees, we characterized linkage disequilibrium structure at the NOS3 locus using 33 common single nucleotide polymorphisms (SNPs). Eighteen SNPs that capture underlying common variation were genotyped in unrelated Framingham Heart Study participants (49.5% women; mean age, 62 years) with measured brachial artery flow-mediated dilation (nϭ1446) or hyperemic flow velocity (nϭ1043). Within 3 defined blocks of strong linkage disequilibrium that spanned NOS3, 11 SNPs captured Ͼ80% of common haplotypic variation. Among men, there were nominally significant associations between 8 NOS3 SNPs (minimum Pϭ0.002) and between haplotypes (minimum Pϭ0.002) and either flow-mediated dilation or hyperemic flow velocity. In women, we did not observe significant associations between NOS3 SNPs or haplotypes and endothelial function measures. To correct for multiple testing, we constructed 1000 bootstrapped null data sets and found that empirical probability values exceeded 0.05 for both phenotypes. Conclusions-A parsimonious set of SNPs captures common genetic variation at the NOS3 locus. A conservative interpretation of our results is that, accounting for multiple testing, we did not observe statistically significant relations between NOS3 sequence variants and endothelial function measures in either sex. The nominal associations of select NOS3 variants with endothelial function in men (unadjusted for multiple testing) should be viewed as hypothesisgenerating observations and may merit testing in other cohorts and experimental designs.

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“…A prospective hypothesis is to assume, one at a time, that every SNP in the initial set could be the disease mutation. The SNP need then not be typed if a tagging SNP in the set provides a given power over the threshold to detect the disease mutation, selecting one of many possible disease models [11,20]. Hu et al [20] defined an alternate measure for calculating power between two SNPs directly from genotypes and without relying on r 2 , as well as different ways to combine the results of all power calculations performed on a region.…”

Section: Pair-wise Metricsmentioning

confidence: 99%

“…A large number of methods have appeared recently in the literature for selecting tagging SNPs [9][10][11][12][13][14][15][16][17][18][19][20]. These differ mostly in two major aspects; the quality or correlation measure used to define tagging, i.e.…”

Section: Haplotype Taggingmentioning

confidence: 99%

Optimal Selection of SNP Markers for Disease Association Studies

Halldórsson¹,

Istrail²,

Vega³

2004

Hum Hered

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Genetic association studies with population samples hold the promise of uncovering the susceptibility genes underlying the heritability of complex or common disease. Most association studies rely on the use of surrogate markers, single-nucleotide polymorphism (SNP) being the most suitable due to their abundance and ease of scoring. SNP marker selection is aimed to increase the chances that at least one typed SNP would be in linkage disequilibrium (LD) with the disease causative variant, while at the same time controlling the cost of the study in terms of the number of markers genotyped and samples. Empirical studies reporting block-like segments in the genome with high LD and low haplotype diversity have motivated a marker selection strategy whereby subsets of SNPs that ‘tag’ the common haplotypes of a region are picked for genotyping, avoiding typing redundant SNPs. Based on these initial observations, a plethora of ‘tagging’ algorithms for selecting minimum informative subsets of SNPs has recently appeared in the literature. These differ mostly in two major aspects: the quality or correlation measure used to define tagging and the algorithm used for the minimization of the final number of tagging SNPs. In this review we describe the available tagging algorithms utilizing a 3-step unifying framework, point out their methodological and conceptual differences, and make an assessment of their assumptions, performance, and scalability.

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SNP Subset Selection for Genetic Association Studies

Cited by 31 publications

References 11 publications

Analysis of multiple SNPs in a candidate gene or region

Analysis of multiple SNPs in a candidate gene or region

Common Genetic Variation at the Endothelial Nitric Oxide Synthase Locus and Relations to Brachial Artery Vasodilator Function in the Community

Optimal Selection of SNP Markers for Disease Association Studies

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