References of "Laird, N. M"
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See detailApproaches to handling incomplete data in family-based association testing
Van Steen, Kristel ULg; Laird, N. M.; Markel, P. et al

in Annals of Human Genetics (2007), 71(Pt 2), 141-51

The high throughput of data arising from the complete sequence of the human genome has left statistical geneticists with a rich and extensive information source. The wide availability of software and the ... [more ▼]

The high throughput of data arising from the complete sequence of the human genome has left statistical geneticists with a rich and extensive information source. The wide availability of software and the increase in computing power has improved the possibilities to access and process such data. One problem is incompleteness of the data: unobserved or partially observed data points due to technical reasons or reasons associated with the patient's status or erroneous measurements of phenotype or genotype, to name a few. When not properly accounted for, these sources of incompleteness may seriously jeopardize the credibility of results from analyses. In this paper we provide some perspectives on the occurrence and analysis of different forms of incomplete data in family-based genetic association testing. [less ▲]

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See detailGenomic screening and replication using the same data set in family-based association testing
Van Steen, Kristel ULg; McQueen, M. B.; Herbert, A. et al

in Nature Genetics (2005), 37(7), 683-691

The Human Genome Project and its spin- offs are making it increasingly feasible to determine the genetic basis of complex traits using genome- wide association studies. The statistical challenge of ... [more ▼]

The Human Genome Project and its spin- offs are making it increasingly feasible to determine the genetic basis of complex traits using genome- wide association studies. The statistical challenge of analyzing such studies stems from the severe multiple-comparison problem resulting from the analysis of thousands of SNPs. Our methodology for genome- wide family- based association studies, using single SNPs or haplotypes, can identify associations that achieve genome- wide significance. In relation to developing guidelines for our screening tools, we determined lower bounds for the estimated power to detect the gene underlying the disease- susceptibility locus, which hold regardless of the linkage disequilibrium structure present in the data. We also assessed the power of our approach in the presence of multiple disease- susceptibility loci. Our screening tools accommodate genomic control and use the concept of haplotype- tagging SNPs. Our methods use the entire sample and do not require separate screening and validation samples to establish genome- wide significance, as population- based designs do. [less ▲]

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See detailCombined analysis from eleven linkage studies of bipolar disorder provides strong evidence of susceptibility loci on chromosomes 6q and 8q
McQueen, M. B.; Devlin, B.; Faraone, S. V. et al

in American Journal of Human Genetics (2005), 77(4), 582-95

Several independent studies and meta-analyses aimed at identifying genomic regions linked to bipolar disorder (BP) have failed to find clear and consistent evidence of linkage regions. Our hypothesis is ... [more ▼]

Several independent studies and meta-analyses aimed at identifying genomic regions linked to bipolar disorder (BP) have failed to find clear and consistent evidence of linkage regions. Our hypothesis is that combining the original genotype data provides benefits of increased power and control over sources of heterogeneity that outweigh the difficulty and potential pitfalls of the implementation. We conducted a combined analysis using the original genotype data from 11 BP genomewide linkage scans comprising 5,179 individuals from 1,067 families. Heterogeneity among studies was minimized in our analyses by using uniform methods of analysis and a common, standardized marker map and was assessed using novel methods developed for meta-analysis of genome scans. To date, this collaboration is the largest and most comprehensive analysis of linkage samples involving a psychiatric disorder. We demonstrate that combining original genome-scan data is a powerful approach for the elucidation of linkage regions underlying complex disease. Our results establish genomewide significant linkage to BP on chromosomes 6q and 8q, which provides solid information to guide future gene-finding efforts that rely on fine-mapping and association approaches. [less ▲]

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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 ▲]

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