Abstract
Many studies have shown that there is a direct relationship between Single Nucleotide Polymorphisms (SNPs) and the appearance of complex diseases, such as Alzheimer’s or Parkinson’s. However, recent advances in the Study of the Complete Genome Association indicate that the relationship between SNPs and these diseases goes beyond a simple one-to-one relationship, that is, the appearance of multiple SNPs (epistasis) influences the appearance of these diseases. In this sense, this work proposes the application of the NSGA-II multi-objective algorithm for the detection of epistasis of multiple loci in a database with 31,341 SNPs. Moreover, a parallel study has been performed to reduce the execution time of this problem. Our implementation not only achieves a reasonable good parallel performance and scalability, but also its biological significance overcomes other approaches published in the literature.
This work was partially funded by the AEI (State Research Agency, Spain) and the ERDF (European Regional Development Fund, EU), under the contract TIN2016-76259-P (PROTEIN project). Thanks also to the Junta de Extremadura and ERDF for the GR15011 grant provided to the group TIC015. Álvaro Rubio-Largo and Sergio Santander-Jiménez are supported by the Post-Doctoral Fellowships SFRH/BPD/100872/2014 and SFRH/BPD/119220/2016 respectively, granted by the FCT (Fundação para a Ciência e a Tecnologia), Portugal.
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Notes
- 1.
A variation in a single nucleotide that occurs at a specific position in the genome.
- 2.
A locus (plural loci) is the position on a chromosome.
- 3.
Expression of the genetic information that owns a particular organism, or genotype.
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Gallego-Sánchez, D., Granado-Criado, J.M., Santander-Jiménez, S., Rubio-Largo, Á., Vega-Rodríguez, M.A. (2017). Parallel Multi-objective Optimization for High-Order Epistasis Detection. In: Ibrahim, S., Choo, KK., Yan, Z., Pedrycz, W. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2017. Lecture Notes in Computer Science(), vol 10393. Springer, Cham. https://doi.org/10.1007/978-3-319-65482-9_38
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