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GenGraph: a python module for the simple generation and manipulation of genome graphs
BACKGROUND: As sequencing technology improves, the concept of a single reference genome is becoming increasingly restricting. In the case of Mycobacterium tuberculosis, one must often choose between using a genome that is closely related to the isolate, or one that is annotated in detail. One promis...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894214/ https://www.ncbi.nlm.nih.gov/pubmed/31653197 http://dx.doi.org/10.1186/s12859-019-3115-8 |
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author | Ambler, Jon Mitchell Mulaudzi, Shandukani Mulder, Nicola |
author_facet | Ambler, Jon Mitchell Mulaudzi, Shandukani Mulder, Nicola |
author_sort | Ambler, Jon Mitchell |
collection | PubMed |
description | BACKGROUND: As sequencing technology improves, the concept of a single reference genome is becoming increasingly restricting. In the case of Mycobacterium tuberculosis, one must often choose between using a genome that is closely related to the isolate, or one that is annotated in detail. One promising solution to this problem is through the graph based representation of collections of genomes as a single genome graph. Though there are currently a handful of tools that can create genome graphs and have demonstrated the advantages of this new paradigm, there still exists a need for flexible tools that can be used by researchers to overcome challenges in genomics studies. RESULTS: We present GenGraph, a Python toolkit and accompanying modules that use existing multiple sequence alignment tools to create genome graphs. Python is one of the most popular coding languages for the biological sciences, and by providing these tools, GenGraph makes it easier to experiment and develop new tools that utilise genome graphs. The conceptual model used is highly intuitive, and as much as possible the graph structure represents the biological relationship between the genomes. This design means that users will quickly be able to start creating genome graphs and using them in their own projects. We outline the methods used in the generation of the graphs, and give some examples of how the created graphs may be used. GenGraph utilises existing file formats and methods in the generation of these graphs, allowing graphs to be visualised and imported with widely used applications, including Cytoscape, R, and Java Script. CONCLUSIONS: GenGraph provides a set of tools for generating graph based representations of sets of sequences with a simple conceptual model, written in the widely used coding language Python, and publicly available on Github. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-3115-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6894214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68942142019-12-11 GenGraph: a python module for the simple generation and manipulation of genome graphs Ambler, Jon Mitchell Mulaudzi, Shandukani Mulder, Nicola BMC Bioinformatics Software BACKGROUND: As sequencing technology improves, the concept of a single reference genome is becoming increasingly restricting. In the case of Mycobacterium tuberculosis, one must often choose between using a genome that is closely related to the isolate, or one that is annotated in detail. One promising solution to this problem is through the graph based representation of collections of genomes as a single genome graph. Though there are currently a handful of tools that can create genome graphs and have demonstrated the advantages of this new paradigm, there still exists a need for flexible tools that can be used by researchers to overcome challenges in genomics studies. RESULTS: We present GenGraph, a Python toolkit and accompanying modules that use existing multiple sequence alignment tools to create genome graphs. Python is one of the most popular coding languages for the biological sciences, and by providing these tools, GenGraph makes it easier to experiment and develop new tools that utilise genome graphs. The conceptual model used is highly intuitive, and as much as possible the graph structure represents the biological relationship between the genomes. This design means that users will quickly be able to start creating genome graphs and using them in their own projects. We outline the methods used in the generation of the graphs, and give some examples of how the created graphs may be used. GenGraph utilises existing file formats and methods in the generation of these graphs, allowing graphs to be visualised and imported with widely used applications, including Cytoscape, R, and Java Script. CONCLUSIONS: GenGraph provides a set of tools for generating graph based representations of sets of sequences with a simple conceptual model, written in the widely used coding language Python, and publicly available on Github. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-3115-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-10-25 /pmc/articles/PMC6894214/ /pubmed/31653197 http://dx.doi.org/10.1186/s12859-019-3115-8 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Ambler, Jon Mitchell Mulaudzi, Shandukani Mulder, Nicola GenGraph: a python module for the simple generation and manipulation of genome graphs |
title | GenGraph: a python module for the simple generation and manipulation of genome graphs |
title_full | GenGraph: a python module for the simple generation and manipulation of genome graphs |
title_fullStr | GenGraph: a python module for the simple generation and manipulation of genome graphs |
title_full_unstemmed | GenGraph: a python module for the simple generation and manipulation of genome graphs |
title_short | GenGraph: a python module for the simple generation and manipulation of genome graphs |
title_sort | gengraph: a python module for the simple generation and manipulation of genome graphs |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894214/ https://www.ncbi.nlm.nih.gov/pubmed/31653197 http://dx.doi.org/10.1186/s12859-019-3115-8 |
work_keys_str_mv | AT amblerjonmitchell gengraphapythonmoduleforthesimplegenerationandmanipulationofgenomegraphs AT mulaudzishandukani gengraphapythonmoduleforthesimplegenerationandmanipulationofgenomegraphs AT muldernicola gengraphapythonmoduleforthesimplegenerationandmanipulationofgenomegraphs |