iHam and pyHam: visualizing and processing hierarchical orthologous groups.

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_8E5F2D47F9B1
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
iHam and pyHam: visualizing and processing hierarchical orthologous groups.
Journal
Bioinformatics
Author(s)
Train C.M., Pignatelli M., Altenhoff A., Dessimoz C.
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Publication state
Published
Issued date
15/07/2019
Peer-reviewed
Oui
Volume
35
Number
14
Pages
2504-2506
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
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'.
Keywords
Biological Evolution, Genome, Software
Pubmed
Web of science
Open Access
Yes
Create date
05/01/2019 17:53
Last modification date
13/01/2021 8:09
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