ArticleNucleic acids research2016
A fast and powerful W-test for pairwise epistasis testing.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed.
- Panel-based targeted exome sequencing reveals novel candidate susceptibility loci for age-related cataracts in Chinese Cohort.Molecular genetics & genomic medicine · 2020Article
- wtest: an integrated R package for genetic epistasis testing.BMC medical genomics · 2019Article
- How to increase our belief in discovered statistical interactions via large-scale association studies?Human genetics · 2019Review
- Robust genetic interaction analysis.Briefings in bioinformatics · 2019Review
- A novel susceptibility locus in MST1 and gene-gene interaction network for Crohn's disease in the Chinese population.Journal of cellular and molecular medicine · 2018Article
- TMEM132: an ancient architecture of cohesin and immunoglobulin domains define a new family of neural adhesion molecules.Bioinformatics (Oxford, England) · 2018Article
- Gene-methylation epistatic analyses via the W-test identifies enriched signals of neuronal genes in patients undergoing lipid-control treatment.BMC proceedings · 2018Article
- Stratified polygenic risk prediction model with application to CAGI bipolar disorder sequencing data.Human mutation · 2017Article
- A Zoom-Focus algorithm (ZFA) to locate the optimal testing region for rare variant association tests.Bioinformatics (Oxford, England) · 2017Article
- Processing closely spaced lesions during Nucleotide Excision Repair triggers mutagenesis in E. coli.PLoS genetics · 2017Article
- Further investigations of the W-test for pairwise epistasis testing.Wellcome open research · 2017Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
Epistasis plays an essential role in the development of complex diseases. Interaction methods face common challenge of seeking a balance between persistent power, model complexity, computation efficiency, and validity of identified bio-markers. We introduce a novel W-test to identify pairwise epistasis effect, which measures the distributional difference between cases and controls through a combined log odds ratio. The test is model-free, fast, and inherits a Chi-squared distribution with data adaptive degrees of freedom. No permutation is needed to obtain the P-values. Simulation studies demonstrated that the W-test is more powerful in low frequency variants environment than alternative methods, which are the Chi-squared test, logistic regression and multifactor-dimensionality reduction (MDR). In two independent real bipolar disorder genome-wide associations (GWAS) datasets, the W-test identified significant interactions pairs that can be replicated, including SLIT3-CENPN, SLIT3-TMEM132D, CNTNAP2-NDST4 and CNTCAP2-RTN4R The genes in the pairs play central roles in neurotransmission and synapse formation. A majority of the identified loci are undiscoverable by main effect and are low frequency variants. The proposed method offers a powerful alternative tool for mapping the genetic puzzle underlying complex disorders.
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Registered trials
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