ArticleGenetic epidemiology2009
Power comparisons between similarity-based multilocus association methods, logistic regression, and score tests for haplotypes.
Article in Genetic epidemiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.Genetic epidemiology · 2015Article
- Generalized functional linear models for gene-based case-control association studies.Genetic epidemiology · 2014Article
- Use of diplotypes - matched haplotype pairs from homologous chromosomes - in gene-disease association studies.Shanghai archives of psychiatry · 2014Article
- GENE-LEVEL PHARMACOGENETIC ANALYSIS ON SURVIVAL OUTCOMES USING GENE-TRAIT SIMILARITY REGRESSION.The annals of applied statistics · 2014Article
- Functional linear models for association analysis of quantitative traits.Genetic epidemiology · 2013Article
- Article
- SNP set association analysis for familial data.Genetic epidemiology · 2012Article
- Haplotype-based methods for detecting uncommon causal variants with common SNPs.Genetic epidemiology · 2012Article
- SNP-set analysis replicates acute lung injury genetic risk factors.BMC medical genetics · 2012Article
- Similarity-based multimarker association tests for continuous traits.Annals of human genetics · 2012Article
- A composite likelihood approach to latent multivariate Gaussian modeling of SNP data with application to genetic association testing.Biometrics · 2012Article
- Multilocus association testing with penalized regression.Genetic epidemiology · 2011Article
- Distance-based phenotypic association analysis of DNA sequence data.BMC proceedings · 2011Article
- Kernel machine SNP-set analysis for censored survival outcomes in genome-wide association studies.Genetic epidemiology · 2011Article
- Comparison of statistical tests for disease association with rare variants.Genetic epidemiology · 2011Article
- Relationship between genomic distance-based regression and kernel machine regression for multi-marker association testing.Genetic epidemiology · 2011Article
- On the Aggregation of Multimarker Information for Marker-Set and Sequencing Data Analysis: Genotype Collapsing vs. Similarity Collapsing.Frontiers in genetics · 2011Article
- Powerful multi-marker association tests: unifying genomic distance-based regression and logistic regression.Genetic epidemiology · 2010Article
- Statistical analysis strategies for association studies involving rare variants.Nature reviews. Genetics · 2010Review
- Discovering joint associations between disease and gene pairs with a novel similarity test.BMC genetics · 2010Article
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2 authors.
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Abstract
Recently, a genomic distance-based regression for multilocus associations was proposed (Wessel and Schork [2006] Am. J. Hum. Genet. 79:792-806) in which either locus or haplotype scoring can be used to measure genetic distance. Although it allows various measures of genomic similarity and simultaneous analyses of multiple phenotypes, its power relative to other methods for case-control analyses is not well known. We compare the power of traditional methods with this new distance-based approach, for both locus-scoring and haplotype-scoring strategies. We discuss the relative power of these association methods with respect to five properties: (1) the marker informativity; (2) the number of markers; (3) the causal allele frequency; (4) the preponderance of the most common high-risk haplotype; (5) the correlation between the causal single-nucleotide polymorphism (SNP) and its flanking markers. We found that locus-based logistic regression and the global score test for haplotypes suffered from power loss when many markers were included in the analyses, due to many degrees of freedom. In contrast, the distance-based approach was not as vulnerable to more markers or more haplotypes. A genotype counting measure was more sensitive to the marker informativity and the correlation between the causal SNP and its flanking markers. After examining the impact of the five properties on power, we found that on average, the genomic distance-based regression that uses a matching measure for diplotypes was the most powerful and robust method among the seven methods we compared.
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