DnoisE: distance denoising by entropy. An open-source parallelizable alternative for denoising sequence datasets
Este artículo contiene 16 páginas, 5 figuras. DNA metabarcoding is broadly used in biodiversity studies encompassing a wide range of organisms. Erroneous amplicons, generated during amplification and sequencing procedures, constitute one of the major sources of concern for the interpretation of meta...
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ftcsic:oai:digital.csic.es:10261/258251 2024-02-11T10:09:29+01:00 DnoisE: distance denoising by entropy. An open-source parallelizable alternative for denoising sequence datasets Antich, Adrià Palacín, Cruz Turon, Xavier Wangensteen, Owen S. 2022 http://hdl.handle.net/10261/258251 en eng PeerJ Publisher's version http://doi.org/10.7717/peerj.12758 Sí PeerJ 10 : e12758 (2022) http://hdl.handle.net/10261/258251 2167-8359 open Metabarcoding Bioinformatic pipelines Metaphylogeography Entropy correction Denoising algorithms Coding markers artículo http://purl.org/coar/resource_type/c_6501 2022 ftcsic https://doi.org/10.7717/peerj.12758 2024-01-16T11:17:37Z Este artículo contiene 16 páginas, 5 figuras. DNA metabarcoding is broadly used in biodiversity studies encompassing a wide range of organisms. Erroneous amplicons, generated during amplification and sequencing procedures, constitute one of the major sources of concern for the interpretation of metabarcoding results. Several denoising programs have been implemented to detect and eliminate these errors. However, almost all denoising software currently available has been designed to process non-coding ribosomal sequences, most notably prokaryotic 16S rDNA. The growing number of metabarcoding studies using coding markers such as COI or RuBisCO demands a re-assessment and calibration of denoising algorithms. Here we present DnoisE, the first denoising program designed to detect erroneous reads and merge them with the correct ones using information from the natural variability (entropy) associated to each codon position in coding barcodes. We have developed an open-source software using a modified version of the UNOISE algorithm. DnoisE implements different merging procedures as options, and can incorporate codon entropy information either retrieved from the data or supplied by the user. In addition, the algorithm of DnoisE is parallelizable, greatly reducing runtimes on computer clusters. Our program also allows different input file formats, so it can be readily incorporated into existing metabarcoding pipelines. This research was funded by the projects PopCOmics (CTM2017-88080, MCIN/AEI/10.13039/ 501100011033 and ``ERDF A way of making Europe'', EU), MARGECH (PID2020- 118550RB, MCIN/AEI/10.13039/501100011033), and BigPark (OAPN, 2462/2017) from the Spanish Government. The publication charges for this article have been funded by a grant from the publication fund of UiT The Arctic University of Norway. Peer reviewed Article in Journal/Newspaper Arctic University of Norway UiT The Arctic University of Norway Digital.CSIC (Spanish National Research Council) Arctic Norway PeerJ 10 e12758 |
institution |
Open Polar |
collection |
Digital.CSIC (Spanish National Research Council) |
op_collection_id |
ftcsic |
language |
English |
topic |
Metabarcoding Bioinformatic pipelines Metaphylogeography Entropy correction Denoising algorithms Coding markers |
spellingShingle |
Metabarcoding Bioinformatic pipelines Metaphylogeography Entropy correction Denoising algorithms Coding markers Antich, Adrià Palacín, Cruz Turon, Xavier Wangensteen, Owen S. DnoisE: distance denoising by entropy. An open-source parallelizable alternative for denoising sequence datasets |
topic_facet |
Metabarcoding Bioinformatic pipelines Metaphylogeography Entropy correction Denoising algorithms Coding markers |
description |
Este artículo contiene 16 páginas, 5 figuras. DNA metabarcoding is broadly used in biodiversity studies encompassing a wide range of organisms. Erroneous amplicons, generated during amplification and sequencing procedures, constitute one of the major sources of concern for the interpretation of metabarcoding results. Several denoising programs have been implemented to detect and eliminate these errors. However, almost all denoising software currently available has been designed to process non-coding ribosomal sequences, most notably prokaryotic 16S rDNA. The growing number of metabarcoding studies using coding markers such as COI or RuBisCO demands a re-assessment and calibration of denoising algorithms. Here we present DnoisE, the first denoising program designed to detect erroneous reads and merge them with the correct ones using information from the natural variability (entropy) associated to each codon position in coding barcodes. We have developed an open-source software using a modified version of the UNOISE algorithm. DnoisE implements different merging procedures as options, and can incorporate codon entropy information either retrieved from the data or supplied by the user. In addition, the algorithm of DnoisE is parallelizable, greatly reducing runtimes on computer clusters. Our program also allows different input file formats, so it can be readily incorporated into existing metabarcoding pipelines. This research was funded by the projects PopCOmics (CTM2017-88080, MCIN/AEI/10.13039/ 501100011033 and ``ERDF A way of making Europe'', EU), MARGECH (PID2020- 118550RB, MCIN/AEI/10.13039/501100011033), and BigPark (OAPN, 2462/2017) from the Spanish Government. The publication charges for this article have been funded by a grant from the publication fund of UiT The Arctic University of Norway. Peer reviewed |
format |
Article in Journal/Newspaper |
author |
Antich, Adrià Palacín, Cruz Turon, Xavier Wangensteen, Owen S. |
author_facet |
Antich, Adrià Palacín, Cruz Turon, Xavier Wangensteen, Owen S. |
author_sort |
Antich, Adrià |
title |
DnoisE: distance denoising by entropy. An open-source parallelizable alternative for denoising sequence datasets |
title_short |
DnoisE: distance denoising by entropy. An open-source parallelizable alternative for denoising sequence datasets |
title_full |
DnoisE: distance denoising by entropy. An open-source parallelizable alternative for denoising sequence datasets |
title_fullStr |
DnoisE: distance denoising by entropy. An open-source parallelizable alternative for denoising sequence datasets |
title_full_unstemmed |
DnoisE: distance denoising by entropy. An open-source parallelizable alternative for denoising sequence datasets |
title_sort |
dnoise: distance denoising by entropy. an open-source parallelizable alternative for denoising sequence datasets |
publisher |
PeerJ |
publishDate |
2022 |
url |
http://hdl.handle.net/10261/258251 |
geographic |
Arctic Norway |
geographic_facet |
Arctic Norway |
genre |
Arctic University of Norway UiT The Arctic University of Norway |
genre_facet |
Arctic University of Norway UiT The Arctic University of Norway |
op_relation |
Publisher's version http://doi.org/10.7717/peerj.12758 Sí PeerJ 10 : e12758 (2022) http://hdl.handle.net/10261/258251 2167-8359 |
op_rights |
open |
op_doi |
https://doi.org/10.7717/peerj.12758 |
container_title |
PeerJ |
container_volume |
10 |
container_start_page |
e12758 |
_version_ |
1790609405998268416 |