SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
ETH Zurich, Department of Computer Science, Zurich, Switzerland.
Bioinformatics. 2019 Jul 15;35(14):2504-2506. doi: 10.1093/bioinformatics/bty994.
The evolutionary history of gene families can be complex due to duplications and losses. This complexity is compounded by the large number of genomes simultaneously considered in contemporary comparative genomic analyses. As provided by several orthology databases, hierarchical orthologous groups (HOGs) are sets of genes that are inferred to have descended from a common ancestral gene within a species clade. This implies that the set of HOGs defined for a particular clade correspond to the ancestral genes found in its last common ancestor. Furthermore, by keeping track of HOG composition along the species tree, it is possible to infer the emergence, duplications and losses of genes within a gene family of interest. However, the lack of tools to manipulate and analyse HOGs has made it difficult to extract, display and interpret this type of information. To address this, we introduce interactive HOG analysis method, an interactive JavaScript widget to visualize and explore gene family history encoded in HOGs and python HOG analysis method, a python library for programmatic processing of genes families. These complementary open source tools greatly ease adoption of HOGs as a scalable and interpretable concept to relate genes across multiple species.
iHam's code is available at https://github.com/DessimozLab/iHam or can be loaded dynamically. pyHam's code is available at https://github.com/DessimozLab/pyHam and or via the pip package 'pyham'.
由于基因的重复和丢失,基因家族的进化历史可能会变得复杂。在当代比较基因组分析中,同时考虑大量基因组,这使得这种复杂性更加复杂。由几个直系同源数据库提供的层次化直系同源群(HOG)是一组基因,这些基因被推断是从一个物种分支内的共同祖先基因中衍生而来的。这意味着为特定分支定义的 HOG 集对应于其最近共同祖先中发现的祖先基因。此外,通过跟踪物种树中 HOG 的组成,可以推断出感兴趣的基因家族中基因的出现、重复和丢失。然而,缺乏操纵和分析 HOG 的工具使得提取、显示和解释这种类型的信息变得困难。为了解决这个问题,我们引入了交互式 HOG 分析方法,这是一个交互式 JavaScript 小部件,用于可视化和探索 HOG 中编码的基因家族历史,以及 python HOG 分析方法,这是一个用于程序化处理基因家族的 python 库。这些互补的开源工具极大地简化了 HOG 作为一种可扩展和可解释的概念,用于在多个物种之间关联基因。
iHam 的代码可在 https://github.com/DessimozLab/iHam 上获得,也可以动态加载。pyHam 的代码可在 https://github.com/DessimozLab/pyHam 上获得,也可以通过 pip 包 'pyham' 获得。