ArticleAmerican journal of human genetics2006
Generalized genomic distance-based regression methodology for multilocus association analysis.
Article in American journal of human genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers, 1 of them a synthesis that pooled it.
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Who cites it
107 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations.PLoS genetics · 2016Pooled it
- Varenicline for smoking cessation: nausea severity and variation in nicotinic receptor genes.The pharmacogenomics journal · 2012Trial
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- General Kernel Machine Methods for Multi-Omics Integration and Genome-Wide Association Testing With Related Individuals.Genetic epidemiology · 2025Article
- BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases.Briefings in bioinformatics · 2024Article
- Excalibur: A new ensemble method based on an optimal combination of aggregation tests for rare-variant association testing for sequencing data.PLoS computational biology · 2023Article
- Interrogating the Human Diplome: Computational Methods, Emerging Applications, and Challenges.Methods in molecular biology (Clifton, N.J.) · 2023Article
- A machine learning-based SNP-set analysis approach for identifying disease-associated susceptibility loci.Scientific reports · 2022Article
- Genotype Value Decomposition: Simple Methods for the Computation of Kernel Statistics.Advanced genetics (Hoboken, N.J.) · 2022Article
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- SPARK-X: non-parametric modeling enables scalable and robust detection of spatial expression patterns for large spatial transcriptomic studies.Genome biology · 2021Article
- A Multi-Marker Test for Analyzing Paired Genetic Data in Transplantation.Frontiers in genetics · 2021Review
- Comparative assessment of genetic diversity matrices and clustering methods in white Guinea yam (Dioscorea rotundata) based on morphological and molecular markers.Scientific reports · 2020Article
- Using association signal annotations to boost similarity network fusion.Bioinformatics (Oxford, England) · 2019Article
- Determining population stratification and subgroup effects in association studies of rare genetic variants for nicotine dependence.Psychiatric genetics · 2019Article
- A review of kernel methods for genetic association studies.Genetic epidemiology · 2019Review
- Detection of epigenetic field defects using a weighted epigenetic distance-based method.Nucleic acids research · 2019Article
- Powerful and robust cross-phenotype association test for case-parent trios.Genetic epidemiology · 2018Article
47 more citing papers are in PubMed but not listed here.
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2 authors.
Funding
Abstract
Large-scale, multilocus genetic association studies require powerful and appropriate statistical-analysis tools that are designed to relate genotype and haplotype information to phenotypes of interest. Many analysis approaches consider relating allelic, haplotypic, or genotypic information to a trait through use of extensions of traditional analysis techniques, such as contingency-table analysis, regression methods, and analysis-of-variance techniques. In this work, we consider a complementary approach that involves the characterization and measurement of the similarity and dissimilarity of the allelic composition of a set of individuals' diploid genomes at multiple loci in the regions of interest. We describe a regression method that can be used to relate variation in the measure of genomic dissimilarity (or "distance") among a set of individuals to variation in their trait values. Weighting factors associated with functional or evolutionary conservation information of the loci can be used in the assessment of similarity. The proposed method is very flexible and is easily extended to complex multilocus-analysis settings involving covariates. In addition, the proposed method actually encompasses both single-locus and haplotype-phylogeny analysis methods, which are two of the most widely used approaches in genetic association analysis. We showcase the method with data described in the literature. Ultimately, our method is appropriate for high-dimensional genomic data and anticipates an era when cost-effective exhaustive DNA sequence data can be obtained for a large number of individuals, over and above genotype information focused on a few well-chosen loci.
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