svist4get: a simple visualization tool for genomic tracks from sequencing experiments
Abstract Background High-throughput sequencing often provides a foundation for experimental analyses in the life sciences. For many such methods, an intermediate layer of bioinformatics data analysis is the genomic signal track constructed by short read mapping to a particular genome assembly. There...
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Format: | Article |
Language: | English |
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BMC
2019-03-01
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Series: | BMC Bioinformatics |
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Online Access: | http://link.springer.com/article/10.1186/s12859-019-2706-8 |
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author | Artyom A. Egorov Ekaterina A. Sakharova Aleksandra S. Anisimova Sergey E. Dmitriev Vadim N. Gladyshev Ivan V. Kulakovskiy |
author_facet | Artyom A. Egorov Ekaterina A. Sakharova Aleksandra S. Anisimova Sergey E. Dmitriev Vadim N. Gladyshev Ivan V. Kulakovskiy |
author_sort | Artyom A. Egorov |
collection | DOAJ |
description | Abstract Background High-throughput sequencing often provides a foundation for experimental analyses in the life sciences. For many such methods, an intermediate layer of bioinformatics data analysis is the genomic signal track constructed by short read mapping to a particular genome assembly. There are many software tools to visualize genomic tracks in a web browser or with a stand-alone graphical user interface. However, there are only few command-line applications suitable for automated usage or production of publication-ready visualizations. Results Here we present svist4get, a command-line tool for customizable generation of publication-quality figures based on data from genomic signal tracks. Similarly to generic genome browser software, svist4get visualizes signal tracks at a given genomic location and is able to aggregate data from several tracks on a single plot along with the transcriptome annotation. The resulting plots can be saved as the vector or high-resolution bitmap images. We demonstrate practical use cases of svist4get for Ribo-Seq and RNA-Seq data. Conclusions svist4get is implemented in Python 3 and runs on Linux. The command-line interface of svist4get allows for easy integration into bioinformatics pipelines in a console environment. Extra customization is possible through configuration files and Python API. For convenience, svist4get is provided as pypi package. The source code is available at https://bitbucket.org/artegorov/svist4get/ |
first_indexed | 2024-12-12T10:42:12Z |
format | Article |
id | doaj.art-20b8108d6ca84cc195bed1c0a372af5d |
institution | Directory Open Access Journal |
issn | 1471-2105 |
language | English |
last_indexed | 2024-12-12T10:42:12Z |
publishDate | 2019-03-01 |
publisher | BMC |
record_format | Article |
series | BMC Bioinformatics |
spelling | doaj.art-20b8108d6ca84cc195bed1c0a372af5d2022-12-22T00:27:00ZengBMCBMC Bioinformatics1471-21052019-03-012011610.1186/s12859-019-2706-8svist4get: a simple visualization tool for genomic tracks from sequencing experimentsArtyom A. Egorov0Ekaterina A. Sakharova1Aleksandra S. Anisimova2Sergey E. Dmitriev3Vadim N. Gladyshev4Ivan V. Kulakovskiy5Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State UniversityVavilov Institute of General Genetics, Russian Academy of SciencesBelozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State UniversityBelozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State UniversityBelozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State UniversityBelozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State UniversityAbstract Background High-throughput sequencing often provides a foundation for experimental analyses in the life sciences. For many such methods, an intermediate layer of bioinformatics data analysis is the genomic signal track constructed by short read mapping to a particular genome assembly. There are many software tools to visualize genomic tracks in a web browser or with a stand-alone graphical user interface. However, there are only few command-line applications suitable for automated usage or production of publication-ready visualizations. Results Here we present svist4get, a command-line tool for customizable generation of publication-quality figures based on data from genomic signal tracks. Similarly to generic genome browser software, svist4get visualizes signal tracks at a given genomic location and is able to aggregate data from several tracks on a single plot along with the transcriptome annotation. The resulting plots can be saved as the vector or high-resolution bitmap images. We demonstrate practical use cases of svist4get for Ribo-Seq and RNA-Seq data. Conclusions svist4get is implemented in Python 3 and runs on Linux. The command-line interface of svist4get allows for easy integration into bioinformatics pipelines in a console environment. Extra customization is possible through configuration files and Python API. For convenience, svist4get is provided as pypi package. The source code is available at https://bitbucket.org/artegorov/svist4get/http://link.springer.com/article/10.1186/s12859-019-2706-8Genomic tracksVisualizationNext-generation sequencingHigh-throughput sequencingRibo-SeqRNA-Seq |
spellingShingle | Artyom A. Egorov Ekaterina A. Sakharova Aleksandra S. Anisimova Sergey E. Dmitriev Vadim N. Gladyshev Ivan V. Kulakovskiy svist4get: a simple visualization tool for genomic tracks from sequencing experiments BMC Bioinformatics Genomic tracks Visualization Next-generation sequencing High-throughput sequencing Ribo-Seq RNA-Seq |
title | svist4get: a simple visualization tool for genomic tracks from sequencing experiments |
title_full | svist4get: a simple visualization tool for genomic tracks from sequencing experiments |
title_fullStr | svist4get: a simple visualization tool for genomic tracks from sequencing experiments |
title_full_unstemmed | svist4get: a simple visualization tool for genomic tracks from sequencing experiments |
title_short | svist4get: a simple visualization tool for genomic tracks from sequencing experiments |
title_sort | svist4get a simple visualization tool for genomic tracks from sequencing experiments |
topic | Genomic tracks Visualization Next-generation sequencing High-throughput sequencing Ribo-Seq RNA-Seq |
url | http://link.springer.com/article/10.1186/s12859-019-2706-8 |
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