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See detailGenomic screening in family-based association testing
Murphy, A.; McGueen, M. B.; Su, J. et al

in Genetic Epidemiology. Supplement (2005), 29

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of ... [more ▼]

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of disease susceptibility loci, and identify new genetic determinants of disease. However, the problem of multiple comparisons threatens to diminish any potential gains from this newly available data. To circumvent the multiple comparisons issue, we utilize a recently developed screening technique using family-based association testing. This screening methodology allows for the identification of the most promising single-nucleotide polymorphisms for testing without biasing the nominal significance level of our test statistic. We compare the results of our screening technique across univariate and multivariate family-based association tests. From our analyses, we observe that the screening technique, applied to different settings, is fairly consistent in identifying optimal markers for testing. One of the identified markers, TSC0047225, was significantly associated with both the ttth1 (p=0.004) and ttth1-ttth4 (p=0.004) phenotype(s). We find that both univariate- and multivariate-based screening techniques are powerful tools for detecting an association. [less ▲]

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See detailComparison of linkage and association strategies for quantitative traits using the COGA dataset.
McQueen, M. B.; Murphy, A.; Kraft, P. et al

in BMC Genetics (2005), 6 Suppl 1

ABSTRACT : Genome scans using dense single-nucleotide polymorphism (SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the ... [more ▼]

ABSTRACT : Genome scans using dense single-nucleotide polymorphism (SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the denser scans will help refine previously identified linkage regions and possibly identify new regions not identifiable using the sparser, microsatellite scans. In the context of the dense SNP scans, it is also possible to consider association strategies to provide even more information about potential regions of interest. To circumvent the multiple-testing issues inherent in association analysis, we use a recently developed strategy, implemented in PBAT, which screens the data to identify the optimal SNPs for testing, without biasing the nominal significance level. We compare the results from the PBAT analysis to that of quantitative linkage analysis on chromosome 4 using the Collaborative Study on the Genetics of Alcoholism data, as released through Genetic Analysis Workshop 14. [less ▲]

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See detailTesting for association in genetic studies
Laird, N. M.; Kraft, P.; Lange, C. et al

in Silverman, E.; Shapiro, S. D.; Lomas, D. A. (Eds.) et al Respiratory Genetics (2005)

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See detailGenomic screening in family-based association testing
Murphy, A.; McGueen, M. B.; Su, J. et al

in BMC Genetics (2005), 6

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of ... [more ▼]

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of disease susceptibility loci, and identify new genetic determinants of disease. However, the problem of multiple comparisons threatens to diminish any potential gains from this newly available data. To circumvent the multiple comparisons issue, we utilize a recently developed screening technique using family-based association testing. This screening methodology allows for the identification of the most promising single-nucleotide polymorphisms for testing without biasing the nominal significance level of our test statistic. We compare the results of our screening technique across univariate and multivariate family-based association tests. From our analyses, we observe that the screening technique, applied to different settings, is fairly consistent in identifying optimal markers for testing. One of the identified markers, TSC0047225, was significantly associated with both the ttth1 (p=0.004) and ttth1-ttth4 (p=0.004) phenotype(s). We find that both univariate- and multivariate-based screening techniques are powerful tools for detecting an association. [less ▲]

Detailed reference viewed: 13 (6 ULg)
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See detailComparison of linkage and association strategies for quantitative traits using the COGA dataset
McQueen, M. B.; Murphy, A.; Kraft, P. et al

in Genetic Epidemiology. Supplement (2005), 29(Suppl I), 1-9

Genome scans using dense single-nucleotide polymorphism ( SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the denser ... [more ▼]

Genome scans using dense single-nucleotide polymorphism ( SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the denser scans will help refine previously identified linkage regions and possibly identify new regions not identifiable using the sparser, microsatellite scans. In the context of the dense SNP scans, it is also possible to consider association strategies to provide even more information about potential regions of interest. To circumvent the multiple-testing issues inherent in association analysis, we use a recently developed strategy, implemented in PBAT, which screens the data to identify the optimal SNPs for testing, without biasing the nominal significance level. We compare the results from the PBAT analysis to that of quantitative linkage analysis on chromosome 4 using the Collaborative Study on the Genetics of Alcoholism data, as released through Genetic Analysis Workshop 14. [less ▲]

Detailed reference viewed: 14 (3 ULg)