ArticleGenetics2008
Kernel-based association test.
Article in Genetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Gene-Based Genome-Wide Association Study Identified Genes for Agronomic Traits in Maize.Biology · 2022Article
- Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits.Scientific reports · 2021Article
- Article
- Combining Partially Overlapping Multi-Omics Data in Databases Using Relationship Matrices.Frontiers in plant science · 2020Article
- OPATs: Omnibus P-value association tests.Briefings in bioinformatics · 2019Review
- Article
- FFBSKAT: fast family-based sequence kernel association test.PloS one · 2014Article
- Comparative Analysis of CNV Calling Algorithms: Literature Survey and a Case Study Using Bovine High-Density SNP Data.Microarrays (Basel, Switzerland) · 2013Review
- The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation.Frontiers in genetics · 2013Article
- Genetic association studies of copy-number variation: should assignment of copy number states precede testing?PloS one · 2012Article
- Article
- Gene-based Higher Criticism methods for large-scale exonic single-nucleotide polymorphism data.BMC proceedings · 2011Article
- Region-based and pathway-based QTL mapping using a p-value combination method.BMC proceedings · 2011Article
- Multilocus association mapping using generalized ridge logistic regression.BMC bioinformatics · 2011Article
- Article
- Predicting genetic values: a kernel-based best linear unbiased prediction with genomic data.Genetics · 2011Article
- Genome-wide gene-based association study.BMC proceedings · 2009Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Association mapping (i.e., linkage disequilibrium mapping) is a powerful tool for positional cloning of disease genes. We propose a kernel-based association test (KBAT), which is a composite function of "P-values of single-locus association tests" and "kernel weights related to intermarker distances and/or linkage disequilibria." The KBAT is a general form of some current test statistics. This method can be applied to the study of candidate genes and can scan each chromosome using a moving average procedure. We evaluated the performance of the KBAT through simulation studies that considered evolutionary parameters, disease models, sample sizes, kernel functions, test statistics, window attributes, empirical P-value estimations, and genetic/physical maps. The results showed that the KBAT had a well-controlled false positive rate and high power compared to existing methods. In addition, the KBAT was also applied to analyze a genomewide data set from the Collaborative Study on the Genetics of Alcoholism. Important genes associated with alcoholism dependence were identified. In summary, the merits of the KBAT are multifold: the KBAT is robust against the inclusion of nuisance markers, is invariant to the map scale, and accommodates different types of genomic data, study designs, and study purposes. The proposed methods are packaged in the user-friendly software, KBAT, available at http://www.stat.sinica.edu.tw/hsinchou/genetics/association/KBAT.htm.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.