基于一致流形逼近和投影的HIV-1逆转录酶选择识别
Identifying Selections Operating on HIV-1 Reverse Transcriptase via Uniform Manifold Approximation and Projection
摘要：
我们分析了来自斯坦福HIV耐药数据库的14，651个标记有治疗方案的HIV 1逆转录酶（HIV RT）序列，以研究这种酶在临床药物选择下的演变。我们的目标是识别正在经历进化的HIV RT序列空间的不同部分，作为识别个体选择和/或进化解决方案的一种方式。我们利用均匀流形近似和投影（UMAP），一个基于图形的降维技术，唯一适合于非线性依赖关系的检测和可视化的结果使用基于密度分析的无监督聚类算法。我们的分析产生了21个不同的序列簇。支持这些簇的生物学意义，它们倾向于代表与不同治疗方案具有强烈对应性的遗传相关序列。因此，这种方法的可视化领域的HIV RT正在演变可以帮助推断信息的选择压力，虽然它是相关的。与每个聚类相关的突变特征可能代表促进这些进化途径的高阶上位性背景，这些信息通常无法通过其他类型的突变共依赖分析获得。
英文摘要：
We analyze 14,651 HIV1 reverse transcriptase (HIV RT) sequences from the Stanford HIV Drug Resistance Database labeled with treatment regimen in order to study the evolution this enzyme under drug selection in the clinic. Our goal is to identify distinct sectors of HIV RT's sequence space that are undergoing evolution as a way to identify individual selections and/or evolutionary solutions. We utilize Uniform Manifold Approximation and Projection (UMAP), a graph-based dimensionality reduction technique uniquely suited for the detection of non-linear dependencies and visualize the results using an unsupervised clustering algorithm based on density analysis. Our analysis produced 21 distinct clusters of sequences. Supporting the biological significance of these clusters, they tend to represent phylogenetically related sequences with strong correspondence to distinct treatment regimens. Thus, this method for visualization of areas of HIV RT undergoing evolution can help infer information about selective pressures, although it is correlative. The mutation signatures associated with each cluster may represent the higher-order epistatic context facilitating these evolutionary pathways, information that is generally not accessible by other types of mutational co-dependence analyses.
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