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Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology

BACKGROUND: Amplicon sequencing of phylogenetic marker genes, e.g., 16S, 18S, or ITS ribosomal RNA sequences, is still the most commonly used method to determine the composition of microbial communities. Microbial ecologists often have expert knowledge on their biological question and data analysis...

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Detalles Bibliográficos
Autores principales: Weißbecker, Christina, Schnabel, Beatrix, Heintz-Buschart, Anna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7702218/
https://www.ncbi.nlm.nih.gov/pubmed/33252655
http://dx.doi.org/10.1093/gigascience/giaa135
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author Weißbecker, Christina
Schnabel, Beatrix
Heintz-Buschart, Anna
author_facet Weißbecker, Christina
Schnabel, Beatrix
Heintz-Buschart, Anna
author_sort Weißbecker, Christina
collection PubMed
description BACKGROUND: Amplicon sequencing of phylogenetic marker genes, e.g., 16S, 18S, or ITS ribosomal RNA sequences, is still the most commonly used method to determine the composition of microbial communities. Microbial ecologists often have expert knowledge on their biological question and data analysis in general, and most research institutes have computational infrastructures to use the bioinformatics command line tools and workflows for amplicon sequencing analysis, but requirements of bioinformatics skills often limit the efficient and up-to-date use of computational resources. RESULTS: We present dadasnake, a user-friendly, 1-command Snakemake pipeline that wraps the preprocessing of sequencing reads and the delineation of exact sequence variants by using the favorably benchmarked and widely used DADA2 algorithm with a taxonomic classification and the post-processing of the resultant tables, including hand-off in standard formats. The suitability of the provided default configurations is demonstrated using mock community data from bacteria and archaea, as well as fungi. CONCLUSIONS: By use of Snakemake, dadasnake makes efficient use of high-performance computing infrastructures. Easy user configuration guarantees flexibility of all steps, including the processing of data from multiple sequencing platforms. It is easy to install dadasnake via conda environments. dadasnake is available at https://github.com/a-h-b/dadasnake.
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spelling pubmed-77022182020-12-07 Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology Weißbecker, Christina Schnabel, Beatrix Heintz-Buschart, Anna Gigascience Technical Note BACKGROUND: Amplicon sequencing of phylogenetic marker genes, e.g., 16S, 18S, or ITS ribosomal RNA sequences, is still the most commonly used method to determine the composition of microbial communities. Microbial ecologists often have expert knowledge on their biological question and data analysis in general, and most research institutes have computational infrastructures to use the bioinformatics command line tools and workflows for amplicon sequencing analysis, but requirements of bioinformatics skills often limit the efficient and up-to-date use of computational resources. RESULTS: We present dadasnake, a user-friendly, 1-command Snakemake pipeline that wraps the preprocessing of sequencing reads and the delineation of exact sequence variants by using the favorably benchmarked and widely used DADA2 algorithm with a taxonomic classification and the post-processing of the resultant tables, including hand-off in standard formats. The suitability of the provided default configurations is demonstrated using mock community data from bacteria and archaea, as well as fungi. CONCLUSIONS: By use of Snakemake, dadasnake makes efficient use of high-performance computing infrastructures. Easy user configuration guarantees flexibility of all steps, including the processing of data from multiple sequencing platforms. It is easy to install dadasnake via conda environments. dadasnake is available at https://github.com/a-h-b/dadasnake. Oxford University Press 2020-11-30 /pmc/articles/PMC7702218/ /pubmed/33252655 http://dx.doi.org/10.1093/gigascience/giaa135 Text en © The Author(s) 2020. Published by Oxford University Press GigaScience. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Technical Note
Weißbecker, Christina
Schnabel, Beatrix
Heintz-Buschart, Anna
Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology
title Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology
title_full Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology
title_fullStr Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology
title_full_unstemmed Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology
title_short Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology
title_sort dadasnake, a snakemake implementation of dada2 to process amplicon sequencing data for microbial ecology
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7702218/
https://www.ncbi.nlm.nih.gov/pubmed/33252655
http://dx.doi.org/10.1093/gigascience/giaa135
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