ArticlePloS one2013
A PLSPM-based test statistic for detecting gene-gene co-association in genome-wide association study with case-control design.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Root anatomical traits modulate the assembly and nitrogen-transformation potential of root-associated microbiomes in a temperate steppe.The New phytologist · 2026Article
- Using Composite Phenotypes to Reveal Hidden Physiological Heterogeneity in High-Altitude Acclimatization in a Chinese Han Longitudinal Cohort.Phenomics (Cham, Switzerland) · 2021Article
- Article
- A gene-based information gain method for detecting gene-gene interactions in case-control studies.European journal of human genetics : EJHG · 2015Article
- Detecting epistasis in human complex traits.Nature reviews. Genetics · 2014Review
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Authors and funding
9 authors.
Funding
Abstract
For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.
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