Billera-Holmes-Vogtmann树空间中核的规范化
Normalizing Kernels in the Billera-Holmes-Vogtmann Treespace
摘要：
随着基因组测序成本的急剧下降，开发有效的生物信息学方法来分析基因组结构和进化变得越来越迫切。例如，大多数已发表的基因组学研究涉及大量序列的串联，或对一小部分正向同源基因推断的同源性进行非正式比较，这两种研究都没有提供进化的全面概述或系统鉴定具有不寻常和有趣进化的基因（例如水平基因转移，基因复制和随后的新功能化）。我们感兴趣的是从一组基因树中识别出这种“外围”基因树，并估计树在“树空间”上的分布。本文介绍了一种改进的kdetrees算法，一个适应经典的核密度估计的度量空间的系统发育树（Billera-Holmes-Vogtman树空间），其中核归一化常数，估计通过使用新的完整梯度方法。作为最初的kdetrees论文，我们已经将kdetrees应用于一组Apicomplexa基因，并确定了几个不可靠的序列比对，这些序列比对已经逃脱了以前的检测，以及一个基因独立报告为水平基因转移的可能情况。
英文摘要：
As costs of genome sequencing have dropped precipitously, development of efficient bioinformatic methods to analyze genome structure and evolution have become ever more urgent. For example, most published phylogenomic studies involve either massive concatenation of sequences, or informal comparisons of phylogenies inferred on a small subset of orthologous genes, neither of which provides a comprehensive overview of evolution or systematic identification of genes with unusual and interesting evolution (e.g. horizontal gene transfers, gene duplication and subsequent neofunctionalization). We are interested in identifying such "outlying" gene trees from the set of gene trees and estimating the distribution of the tree over the "tree space". This paper describes an improvement to the kdetrees algorithm, an adaptation of classical kernel density estimation to the metric space of phylogenetic trees (Billera-Holmes-Vogtman treespace), whereby the kernel normalizing constants, are estimated through the use of the novel holonomic gradient methods. As the original kdetrees paper, we have applied kdetrees to a set of Apicomplexa genes and it identified several unreliable sequence alignments which had escaped previous detection, as well as a gene independently reported as a possible case of horizontal gene transfer.
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