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NGSNGS: next-generation simulator for next-generation sequencing data
SUMMARY: With the rapid expansion of the capabilities of the DNA sequencers throughout the different sequencing generations, the quantity of generated data has likewise increased. This evolution has also led to new bioinformatical methods, for which in silico data have become crucial when verifying...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9891242/ https://www.ncbi.nlm.nih.gov/pubmed/36661298 http://dx.doi.org/10.1093/bioinformatics/btad041 |
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author | Henriksen, Rasmus Amund Zhao, Lei Korneliussen, Thorfinn Sand |
author_facet | Henriksen, Rasmus Amund Zhao, Lei Korneliussen, Thorfinn Sand |
author_sort | Henriksen, Rasmus Amund |
collection | PubMed |
description | SUMMARY: With the rapid expansion of the capabilities of the DNA sequencers throughout the different sequencing generations, the quantity of generated data has likewise increased. This evolution has also led to new bioinformatical methods, for which in silico data have become crucial when verifying the accuracy of a model or the robustness of a genomic analysis pipeline. Here, we present a multithreaded next-generation simulator for next-generation sequencing data (NGSNGS), which simulates reads faster than currently available methods and programs. NGSNGS can simulate reads with platform-specific characteristics based on nucleotide quality score profiles as well as including a post-mortem damage model which is relevant for simulating ancient DNA. The simulated sequences are sampled (with replacement) from a reference DNA genome, which can represent a haploid genome, polyploid assemblies or even population haplotypes and allows the user to simulate known variable sites directly. The program is implemented in a multithreading framework and is factors faster than currently available tools while extending their feature set and possible output formats. AVAILABILITY AND IMPLEMENTATION: The method and associated programs are released as open-source software, code and user manual are available at https://github.com/RAHenriksen/NGSNGS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9891242 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98912422023-02-02 NGSNGS: next-generation simulator for next-generation sequencing data Henriksen, Rasmus Amund Zhao, Lei Korneliussen, Thorfinn Sand Bioinformatics Applications Note SUMMARY: With the rapid expansion of the capabilities of the DNA sequencers throughout the different sequencing generations, the quantity of generated data has likewise increased. This evolution has also led to new bioinformatical methods, for which in silico data have become crucial when verifying the accuracy of a model or the robustness of a genomic analysis pipeline. Here, we present a multithreaded next-generation simulator for next-generation sequencing data (NGSNGS), which simulates reads faster than currently available methods and programs. NGSNGS can simulate reads with platform-specific characteristics based on nucleotide quality score profiles as well as including a post-mortem damage model which is relevant for simulating ancient DNA. The simulated sequences are sampled (with replacement) from a reference DNA genome, which can represent a haploid genome, polyploid assemblies or even population haplotypes and allows the user to simulate known variable sites directly. The program is implemented in a multithreading framework and is factors faster than currently available tools while extending their feature set and possible output formats. AVAILABILITY AND IMPLEMENTATION: The method and associated programs are released as open-source software, code and user manual are available at https://github.com/RAHenriksen/NGSNGS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2023-01-20 /pmc/articles/PMC9891242/ /pubmed/36661298 http://dx.doi.org/10.1093/bioinformatics/btad041 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Henriksen, Rasmus Amund Zhao, Lei Korneliussen, Thorfinn Sand NGSNGS: next-generation simulator for next-generation sequencing data |
title | NGSNGS: next-generation simulator for next-generation sequencing data |
title_full | NGSNGS: next-generation simulator for next-generation sequencing data |
title_fullStr | NGSNGS: next-generation simulator for next-generation sequencing data |
title_full_unstemmed | NGSNGS: next-generation simulator for next-generation sequencing data |
title_short | NGSNGS: next-generation simulator for next-generation sequencing data |
title_sort | ngsngs: next-generation simulator for next-generation sequencing data |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9891242/ https://www.ncbi.nlm.nih.gov/pubmed/36661298 http://dx.doi.org/10.1093/bioinformatics/btad041 |
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