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SAMSA2: a standalone metatranscriptome analysis pipeline
BACKGROUND: Complex microbial communities are an area of growing interest in biology. Metatranscriptomics allows researchers to quantify microbial gene expression in an environmental sample via high-throughput sequencing. Metatranscriptomic experiments are computationally intensive because the exper...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5963165/ https://www.ncbi.nlm.nih.gov/pubmed/29783945 http://dx.doi.org/10.1186/s12859-018-2189-z |
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author | Westreich, Samuel T. Treiber, Michelle L. Mills, David A. Korf, Ian Lemay, Danielle G. |
author_facet | Westreich, Samuel T. Treiber, Michelle L. Mills, David A. Korf, Ian Lemay, Danielle G. |
author_sort | Westreich, Samuel T. |
collection | PubMed |
description | BACKGROUND: Complex microbial communities are an area of growing interest in biology. Metatranscriptomics allows researchers to quantify microbial gene expression in an environmental sample via high-throughput sequencing. Metatranscriptomic experiments are computationally intensive because the experiments generate a large volume of sequence data and each sequence must be compared with reference sequences from thousands of organisms. RESULTS: SAMSA2 is an upgrade to the original Simple Annotation of Metatranscriptomes by Sequence Analysis (SAMSA) pipeline that has been redesigned for standalone use on a supercomputing cluster. SAMSA2 is faster due to the use of the DIAMOND aligner, and more flexible and reproducible because it uses local databases. SAMSA2 is available with detailed documentation, and example input and output files along with examples of master scripts for full pipeline execution. CONCLUSIONS: SAMSA2 is a rapid and efficient metatranscriptome pipeline for analyzing large RNA-seq datasets in a supercomputing cluster environment. SAMSA2 provides simplified output that can be examined directly or used for further analyses, and its reference databases may be upgraded, altered or customized to fit the needs of any experiment. |
format | Online Article Text |
id | pubmed-5963165 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59631652018-05-24 SAMSA2: a standalone metatranscriptome analysis pipeline Westreich, Samuel T. Treiber, Michelle L. Mills, David A. Korf, Ian Lemay, Danielle G. BMC Bioinformatics Software BACKGROUND: Complex microbial communities are an area of growing interest in biology. Metatranscriptomics allows researchers to quantify microbial gene expression in an environmental sample via high-throughput sequencing. Metatranscriptomic experiments are computationally intensive because the experiments generate a large volume of sequence data and each sequence must be compared with reference sequences from thousands of organisms. RESULTS: SAMSA2 is an upgrade to the original Simple Annotation of Metatranscriptomes by Sequence Analysis (SAMSA) pipeline that has been redesigned for standalone use on a supercomputing cluster. SAMSA2 is faster due to the use of the DIAMOND aligner, and more flexible and reproducible because it uses local databases. SAMSA2 is available with detailed documentation, and example input and output files along with examples of master scripts for full pipeline execution. CONCLUSIONS: SAMSA2 is a rapid and efficient metatranscriptome pipeline for analyzing large RNA-seq datasets in a supercomputing cluster environment. SAMSA2 provides simplified output that can be examined directly or used for further analyses, and its reference databases may be upgraded, altered or customized to fit the needs of any experiment. BioMed Central 2018-05-21 /pmc/articles/PMC5963165/ /pubmed/29783945 http://dx.doi.org/10.1186/s12859-018-2189-z Text en © The Author(s). 2018 Open AccessThis 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 Westreich, Samuel T. Treiber, Michelle L. Mills, David A. Korf, Ian Lemay, Danielle G. SAMSA2: a standalone metatranscriptome analysis pipeline |
title | SAMSA2: a standalone metatranscriptome analysis pipeline |
title_full | SAMSA2: a standalone metatranscriptome analysis pipeline |
title_fullStr | SAMSA2: a standalone metatranscriptome analysis pipeline |
title_full_unstemmed | SAMSA2: a standalone metatranscriptome analysis pipeline |
title_short | SAMSA2: a standalone metatranscriptome analysis pipeline |
title_sort | samsa2: a standalone metatranscriptome analysis pipeline |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5963165/ https://www.ncbi.nlm.nih.gov/pubmed/29783945 http://dx.doi.org/10.1186/s12859-018-2189-z |
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