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DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing

MOTIVATION: Nanopore sequencing is one of the leading third-generation sequencing technologies. A number of computational tools have been developed to facilitate the processing and analysis of the Nanopore data. Previously, we have developed DeepSimulator1.0 (DS1.0), which is the first simulator for...

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Autores principales: Li, Yu, Wang, Sheng, Bi, Chongwei, Qiu, Zhaowen, Li, Mo, Gao, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7178411/
https://www.ncbi.nlm.nih.gov/pubmed/31913436
http://dx.doi.org/10.1093/bioinformatics/btz963
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author Li, Yu
Wang, Sheng
Bi, Chongwei
Qiu, Zhaowen
Li, Mo
Gao, Xin
author_facet Li, Yu
Wang, Sheng
Bi, Chongwei
Qiu, Zhaowen
Li, Mo
Gao, Xin
author_sort Li, Yu
collection PubMed
description MOTIVATION: Nanopore sequencing is one of the leading third-generation sequencing technologies. A number of computational tools have been developed to facilitate the processing and analysis of the Nanopore data. Previously, we have developed DeepSimulator1.0 (DS1.0), which is the first simulator for Nanopore sequencing to produce both the raw electrical signals and the reads. However, although DS1.0 can produce high-quality reads, for some sequences, the divergence between the simulated raw signals and the real signals can be large. Furthermore, the Nanopore sequencing technology has evolved greatly since DS1.0 was released. It is thus necessary to update DS1.0 to accommodate those changes. RESULTS: We propose DeepSimulator1.5 (DS1.5), all three modules of which have been updated substantially from DS1.0. As for the sequence generator, we updated the sample read length distribution to reflect the newest real reads’ features. In terms of the signal generator, which is the core of DeepSimulator, we added one more pore model, the context-independent pore model, which is much faster than the previous context-dependent one. Furthermore, to make the generated signals more similar to the real ones, we added a low-pass filter to post-process the pore model signals. Regarding the basecaller, we added the support for the newest official basecaller, Guppy, which can support both GPU and CPU. In addition, multiple optimizations, related to multiprocessing control, memory and storage management, have been implemented to make DS1.5 a much more amenable and lighter simulator than DS1.0. AVAILABILITY AND IMPLEMENTATION: The main program and the data are available at https://github.com/lykaust15/DeepSimulator. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-71784112020-04-28 DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing Li, Yu Wang, Sheng Bi, Chongwei Qiu, Zhaowen Li, Mo Gao, Xin Bioinformatics Applications Notes MOTIVATION: Nanopore sequencing is one of the leading third-generation sequencing technologies. A number of computational tools have been developed to facilitate the processing and analysis of the Nanopore data. Previously, we have developed DeepSimulator1.0 (DS1.0), which is the first simulator for Nanopore sequencing to produce both the raw electrical signals and the reads. However, although DS1.0 can produce high-quality reads, for some sequences, the divergence between the simulated raw signals and the real signals can be large. Furthermore, the Nanopore sequencing technology has evolved greatly since DS1.0 was released. It is thus necessary to update DS1.0 to accommodate those changes. RESULTS: We propose DeepSimulator1.5 (DS1.5), all three modules of which have been updated substantially from DS1.0. As for the sequence generator, we updated the sample read length distribution to reflect the newest real reads’ features. In terms of the signal generator, which is the core of DeepSimulator, we added one more pore model, the context-independent pore model, which is much faster than the previous context-dependent one. Furthermore, to make the generated signals more similar to the real ones, we added a low-pass filter to post-process the pore model signals. Regarding the basecaller, we added the support for the newest official basecaller, Guppy, which can support both GPU and CPU. In addition, multiple optimizations, related to multiprocessing control, memory and storage management, have been implemented to make DS1.5 a much more amenable and lighter simulator than DS1.0. AVAILABILITY AND IMPLEMENTATION: The main program and the data are available at https://github.com/lykaust15/DeepSimulator. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-04-15 2020-01-08 /pmc/articles/PMC7178411/ /pubmed/31913436 http://dx.doi.org/10.1093/bioinformatics/btz963 Text en © The Author(s) 2020. Published by Oxford University Press. 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 Applications Notes
Li, Yu
Wang, Sheng
Bi, Chongwei
Qiu, Zhaowen
Li, Mo
Gao, Xin
DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing
title DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing
title_full DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing
title_fullStr DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing
title_full_unstemmed DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing
title_short DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing
title_sort deepsimulator1.5: a more powerful, quicker and lighter simulator for nanopore sequencing
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7178411/
https://www.ncbi.nlm.nih.gov/pubmed/31913436
http://dx.doi.org/10.1093/bioinformatics/btz963
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