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SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses
MOTIVATION: Modern molecular methods have increased our ability to describe microbial communities. Along with the advances brought by new sequencing technologies, we now require intensive computational resources to make sense of the large numbers of sequences continuously produced. The software deve...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022770/ https://www.ncbi.nlm.nih.gov/pubmed/29452334 http://dx.doi.org/10.1093/bioinformatics/bty071 |
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author | Větrovský, Tomáš Baldrian, Petr Morais, Daniel |
author_facet | Větrovský, Tomáš Baldrian, Petr Morais, Daniel |
author_sort | Větrovský, Tomáš |
collection | PubMed |
description | MOTIVATION: Modern molecular methods have increased our ability to describe microbial communities. Along with the advances brought by new sequencing technologies, we now require intensive computational resources to make sense of the large numbers of sequences continuously produced. The software developed by the scientific community to address this demand, although very useful, require experience of the command-line environment, extensive training and have steep learning curves, limiting their use. We created SEED 2, a graphical user interface for handling high-throughput amplicon-sequencing data under Windows operating systems. RESULTS: SEED 2 is the only sequence visualizer that empowers users with tools to handle amplicon-sequencing data of microbial community markers. It is suitable for any marker genes sequences obtained through Illumina, IonTorrent or Sanger sequencing. SEED 2 allows the user to process raw sequencing data, identify specific taxa, produce of OTU-tables, create sequence alignments and construct phylogenetic trees. Standard dual core laptops with 8 GB of RAM can handle ca. 8 million of Illumina PE 300 bp sequences, ca. 4 GB of data. AVAILABILITY AND IMPLEMENTATION: SEED 2 was implemented in Object Pascal and uses internal functions and external software for amplicon data processing. SEED 2 is a freeware software, available at http://www.biomed.cas.cz/mbu/lbwrf/seed/ as a self-contained file, including all the dependencies, and does not require installation. Supplementary data contain a comprehensive list of supported functions. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6022770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60227702018-07-05 SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses Větrovský, Tomáš Baldrian, Petr Morais, Daniel Bioinformatics Applications Notes MOTIVATION: Modern molecular methods have increased our ability to describe microbial communities. Along with the advances brought by new sequencing technologies, we now require intensive computational resources to make sense of the large numbers of sequences continuously produced. The software developed by the scientific community to address this demand, although very useful, require experience of the command-line environment, extensive training and have steep learning curves, limiting their use. We created SEED 2, a graphical user interface for handling high-throughput amplicon-sequencing data under Windows operating systems. RESULTS: SEED 2 is the only sequence visualizer that empowers users with tools to handle amplicon-sequencing data of microbial community markers. It is suitable for any marker genes sequences obtained through Illumina, IonTorrent or Sanger sequencing. SEED 2 allows the user to process raw sequencing data, identify specific taxa, produce of OTU-tables, create sequence alignments and construct phylogenetic trees. Standard dual core laptops with 8 GB of RAM can handle ca. 8 million of Illumina PE 300 bp sequences, ca. 4 GB of data. AVAILABILITY AND IMPLEMENTATION: SEED 2 was implemented in Object Pascal and uses internal functions and external software for amplicon data processing. SEED 2 is a freeware software, available at http://www.biomed.cas.cz/mbu/lbwrf/seed/ as a self-contained file, including all the dependencies, and does not require installation. Supplementary data contain a comprehensive list of supported functions. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-07-01 2018-02-14 /pmc/articles/PMC6022770/ /pubmed/29452334 http://dx.doi.org/10.1093/bioinformatics/bty071 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Větrovský, Tomáš Baldrian, Petr Morais, Daniel SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses |
title | SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses |
title_full | SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses |
title_fullStr | SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses |
title_full_unstemmed | SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses |
title_short | SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses |
title_sort | seed 2: a user-friendly platform for amplicon high-throughput sequencing data analyses |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022770/ https://www.ncbi.nlm.nih.gov/pubmed/29452334 http://dx.doi.org/10.1093/bioinformatics/bty071 |
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