Flower Pollination Algorithm for Detection of Epistasis Associated with a Phenotype

Sitarcik, J.¹, Lucka, M., Krajcovic, T.¹

¹ Faculty of Informatics and Information Technologies, Slovak University of Technology, Ilkovicova 2, Bratislava, Slovakia

Detecting associations of SNPs with traits like complex diseases can provide valuable insights. However, due to the epistases – complex interactions between SNPs – SNP combinations need to be evaluated for their association with a trait. As the number of possible SNP combinations grows rapidly with increase of the number of SNPs, great computational challenges have to be tackled. In this paper, we propose FPepi, epistasis detection tool based on flower pollination algorithm with multiple objectives. Two variants of the algorithm are proposed, one using Gini score and K2 score as objectives, while the second variant uses K2 score and mutual information score. The flower pollination algorithm selects a small subset of potential SNP combinations, that are then evaluated by G-test. The proposed tool shown better results in detection power when compared with other similar tools.

Cite: Sitarcik, J., Lucka, M., Krajcovic, T. Flower Pollination Algorithm for Detection of Epistasis Associated with a Phenotype. Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies – BIOINFORMATICS (2021). DOI: 10.5220/0010254501180126