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Ariadne: synthetic long read deconvolution using assembly graphs
Synthetic long read sequencing techniques such as UST’s TELL-Seq and Loop Genomics’ LoopSeq combine 3[Formula: see text] barcoding with standard short-read sequencing to expand the range of linkage resolution from hundreds to tens of thousands of base-pairs. However, the lack of a 1:1 correspondence...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463629/ https://www.ncbi.nlm.nih.gov/pubmed/37641111 http://dx.doi.org/10.1186/s13059-023-03033-5 |
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author | Mak, Lauren Meleshko, Dmitry Danko, David C. Barakzai, Waris N. Maharjan, Salil Belchikov, Natan Hajirasouliha, Iman |
author_facet | Mak, Lauren Meleshko, Dmitry Danko, David C. Barakzai, Waris N. Maharjan, Salil Belchikov, Natan Hajirasouliha, Iman |
author_sort | Mak, Lauren |
collection | PubMed |
description | Synthetic long read sequencing techniques such as UST’s TELL-Seq and Loop Genomics’ LoopSeq combine 3[Formula: see text] barcoding with standard short-read sequencing to expand the range of linkage resolution from hundreds to tens of thousands of base-pairs. However, the lack of a 1:1 correspondence between a long fragment and a 3[Formula: see text] unique molecular identifier confounds the assignment of linkage between short reads. We introduce Ariadne, a novel assembly graph-based synthetic long read deconvolution algorithm, that can be used to extract single-species read-clouds from synthetic long read datasets to improve the taxonomic classification and de novo assembly of complex populations, such as metagenomes. |
format | Online Article Text |
id | pubmed-10463629 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-104636292023-08-30 Ariadne: synthetic long read deconvolution using assembly graphs Mak, Lauren Meleshko, Dmitry Danko, David C. Barakzai, Waris N. Maharjan, Salil Belchikov, Natan Hajirasouliha, Iman Genome Biol Method Synthetic long read sequencing techniques such as UST’s TELL-Seq and Loop Genomics’ LoopSeq combine 3[Formula: see text] barcoding with standard short-read sequencing to expand the range of linkage resolution from hundreds to tens of thousands of base-pairs. However, the lack of a 1:1 correspondence between a long fragment and a 3[Formula: see text] unique molecular identifier confounds the assignment of linkage between short reads. We introduce Ariadne, a novel assembly graph-based synthetic long read deconvolution algorithm, that can be used to extract single-species read-clouds from synthetic long read datasets to improve the taxonomic classification and de novo assembly of complex populations, such as metagenomes. BioMed Central 2023-08-28 /pmc/articles/PMC10463629/ /pubmed/37641111 http://dx.doi.org/10.1186/s13059-023-03033-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Method Mak, Lauren Meleshko, Dmitry Danko, David C. Barakzai, Waris N. Maharjan, Salil Belchikov, Natan Hajirasouliha, Iman Ariadne: synthetic long read deconvolution using assembly graphs |
title | Ariadne: synthetic long read deconvolution using assembly graphs |
title_full | Ariadne: synthetic long read deconvolution using assembly graphs |
title_fullStr | Ariadne: synthetic long read deconvolution using assembly graphs |
title_full_unstemmed | Ariadne: synthetic long read deconvolution using assembly graphs |
title_short | Ariadne: synthetic long read deconvolution using assembly graphs |
title_sort | ariadne: synthetic long read deconvolution using assembly graphs |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463629/ https://www.ncbi.nlm.nih.gov/pubmed/37641111 http://dx.doi.org/10.1186/s13059-023-03033-5 |
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