ArticleCurrent genomics2013
Gene-based Genomewide Association Analysis: A Comparison Study.
Article in Current genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Different genes may be involved in distal and local sensitization: A genome-wide gene-based association study and meta-analysis.European journal of pain (London, England) · 2022Pooled it
- LDAK-GBAT: Fast and powerful gene-based association testing using summary statistics.American journal of human genetics · 2023Article
- Identification of novel genes for triple-negative breast cancer with semiparametric gene-based analysis.Journal of applied statistics · 2023Article
- Genetic association-based functional analysis detectsFrontiers in genetics · 2022Article
- Genome-Wide Association Study of Latent Cognitive Measures in Adolescence: Genetic Overlap With Intelligence and Education.Mind, brain and education : the official journal of the International Mind, Brain, and Education Society · 2019Article
- Phenotypic and Genomic Local Adaptation across Latitude and Altitude in Populus trichocarpa.Genome biology and evolution · 2019Article
- Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle.BMC genomics · 2018Article
- Gene-based analysis of genes related to neurotrophic pathway suggests association of BDNF and VEGFA with antidepressant treatment-response in depressed patients.Scientific reports · 2018Article
- Multi-strategy genome-wide association studies identify the DCAF16-NCAPG region as a susceptibility locus for average daily gain in cattle.Scientific reports · 2016Article
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Corrections and comments
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3 authors.
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Abstract
The study of gene-based genetic associations has gained conceptual popularity recently. Biologic insight into the etiology of a complex disease can be gained by focusing on genes as testing units. Several gene-based methods (e.g., minimum p-value (or maximum test statistic) or entropy-based method) have been developed and have more power than a single nucleotide polymorphism (SNP)-based analysis. The objective of this study is to compare the performance of the entropy-based method with the minimum p-value and single SNP-based analysis and to explore their strengths and weaknesses. Simulation studies show that: 1) all three methods can reasonably control the false-positive rate; 2) the minimum p-value method outperforms the entropy-based and the single SNP-based method when only one disease-related SNP occurs within the gene; 3) the entropy-based method outperforms the other methods when there are more than two disease-related SNPs in the gene; and 4) the entropy-based method is computationally more efficient than the minimum p-value method. Application to a real data set shows that more significant genes were identified by the entropy-based method than by the other two methods.
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