ArticleBMC genetics2013
The complete compositional epistasis detection in genome-wide association studies.
Article in BMC genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Genetic dissection of the gene coexpression network underlying photosynthesis in Populus.Plant biotechnology journal · 2020Article
- Article
- Collective feature selection to identify crucial epistatic variants.BioData mining · 2018Article
- Representing annotation compositionality and provenance for the Semantic Web.Journal of biomedical semantics · 2013Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe detection of epistasis among genetic markers is of great interest in genome-wide association studies (GWAS). In recent years, much research has been devoted to find disease-associated epistasis in GWAS. However, due to the high computational cost involved, most methods focus on specific epistasis models, making the potential loss of power when the underlying epistasis models are not examined in these analyses.
resultsIn this work, we propose a computational efficient approach based on complete enumeration of two-locus epistasis models. This approach uses a two-stage (screening and testing) search strategy and guarantees the enumeration of all epistasis patterns. The implementation is done on graphic processing units (GPU), which can finish the analysis on a GWAS data (with around 5,000 subjects and around 350,000 markers) within two hours. Source code is available at http://bioinformatics.ust.hk/BOOST.html#GBOOST.
conclusionsThis work demonstrates that the complete compositional epistasis detection is computationally feasible in GWAS.
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