Epistasis analysis reveals associations between gene variants and bipolar disorder
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Biology
- Keywords
- Epistasis, variant interactions, complex phenotypes, genotype/phenotype association
- Copyright
- © 2017 Maj et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. Epistasis analysis reveals associations between gene variants and bipolar disorder. PeerJ Preprints 5:e3242v1 https://doi.org/10.7287/peerj.preprints.3242v1
Abstract
In complex phenotypes (e.g., psychiatric diseases) single locus tests, commonly performed with Genome-Wide Association Studies, have proven to be limited in discovering strong gene associations. A growing body of evidence suggests that epistatic non-linear effects may be responsible for complex phenotypes arising from the interaction of different biological factors. A major issue in epistasis analysis is the computational burden due to the huge number of statistical tests to be performed when considering all the potential genotype combinations. In this work, we developed a computational efficient pipeline to investigate the presence of epistasis at a genome-wide scale in bipolar disorder, which is a typical example of complex phenotype with a relevant but unexplained genetic background. By running our pipeline we were able to identify 13 epistasis interactions between variants located in genes potentially involved in biological processes associated with the analyzed phenotype.
Author Comment
This work is part of the NETTAB 2017 Workshop Collection.