目的：改进经典蚁群聚类算法（LF算法），应用到盐敏性高血压SNPs数据分析，为探讨高通量SNPs统计分析提供新思路。方法：改进LF算法，利用Matlab8.0软件对改进后算法进行编程，对335个盐敏性高血压样本进行聚类分析，并通过潜在类别分析的结果进行比较。结果：成功改进LF算法并实现软件化界面。采用新算法将所有样本分成2个类别，第一类169份样本，第二类166份样本，与潜在类别分析法结果进行一致性检验，Kappa值为0.93，P<0.001，并通过两类人群SNPs概率分布差异统计学检验，筛选出3个SNPs：rs848307、rs1739843、rs1010069，明确其在分类中的重要作用。结论：蚁群聚类算法具有思维独特、计算自动化、易于改进等特点，在高通量SNPs数据分析及其他基因组学相关领域有广阔的应用前景。%Objective: Improved classical ant colony clustering algorithm applied to salt-sensitive hypertension single nucleotide polymorphism data analysis, high-throughput SNPs investigate complex diseases statistical analysis provides a new approach to support. Methods Performed classical ant colony clustering algorithm optimized for improved Matlab8.0 software using the improved algorithm can be programmed for 335 salt-sensitive hypertension samples containing 29 SNPs cluster analysis data, and through potential category results of the analysis were compared and evaluated the improved algorithm.Results Improved ant colony algorithm to establish and implement the software interface. Using this algorithm, al the samples successful y into two categories, the first class of 169 samples (50.4%), the second 166 samples (49.6%). Using latent class analysis Cluster analysis results obtained for the first class 174 samples (51.9%), the second 158 samples (47.1%). Both methods consistency test, Kappa value 0.93, P<0.001, and the distribution of the difference between the probability of significant SNPs tested by two populations screened in 29 SNPs rs848307, rs1739843, rs10100693 SNPs in its important role in the classification. Conclusion Improved ant colony clustering algorithm has unique thinking, computing automation, easy to improve other characteristics, form their own advantage, SNPs in high-throughput data analysis and other related fields of genomics has broad application prospects.
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