基于蚁群算法的基因位点组合与眼压数据的相关性分析

设计了一种蚁群算法，用于进行基因多位点组合与连续型表型的关联分析。在欧洲生物信息学研究所发布的一项基因及眼压的数据集上，评估了本文设计方法的性能，实验结果表明，利用本文设计的蚁群算法能够发现与眼压显著相关的基因双位点组合，这为研究青光眼的发病机制提供了新的线索。另外，对于研究其他疾病的多位点组合和连续型表型的关联，本文设计的蚁群算法提供了一种新的思路。

Correlation analysis between gene locus combinations and intraocular pressure data based on ant colony algorithms

The association analysis of multi-site combinations and phenotype of genes is a research hotspot in bioinformatics studies. Recent studies have shown that for complex genetic diseases, multi-site combinations are more significantly associated with phenotypes than single gene-specific points. However, the existing methods are only suitable for analyzing the association of multi-site combinations with discrete phenotypes, and cannot analyze the association with continuous phenotypes. Glaucoma is the second most common cause of irreversible blindness. High intraocular pressure is the most important indication of the onset of glaucoma. Therefore, studying the correlation between multi-site combination and intraocular pressure is of great significance for studying the pathogenesis of glaucoma. In this paper, an ant colony algorithm has been designed to study the association analysis between gene multi-site combinations and continuous phenotypes. In this work, we evaluated the performance of a method designed by ourselves on a gene and intraocular pressure dataset published by the European Institute of Bioinformatics. The experimental results show that the ant colony algorithm developed in this work can find the two-point combinations of genes significantly related to intraocular pressure, which might provide new clues for studying the pathogenesis of glaucoma. In addition, the ant colony algorithm devoloped in this work provides new ideas for studying the association of multi-site combinations and continuous phenotypes in other diseases.