Cargando…
PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores
MOTIVATION: Recent advances in high-throughput long-read sequencers, such as PacBio and Oxford Nanopore sequencers, produce longer reads with more errors than short-read sequencers. In addition to the high error rates of reads, non-uniformity of errors leads to difficulties in various downstream ana...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097687/ https://www.ncbi.nlm.nih.gov/pubmed/32976553 http://dx.doi.org/10.1093/bioinformatics/btaa835 |
_version_ | 1783688369088233472 |
---|---|
author | Ono, Yukiteru Asai, Kiyoshi Hamada, Michiaki |
author_facet | Ono, Yukiteru Asai, Kiyoshi Hamada, Michiaki |
author_sort | Ono, Yukiteru |
collection | PubMed |
description | MOTIVATION: Recent advances in high-throughput long-read sequencers, such as PacBio and Oxford Nanopore sequencers, produce longer reads with more errors than short-read sequencers. In addition to the high error rates of reads, non-uniformity of errors leads to difficulties in various downstream analyses using long reads. Many useful simulators, which characterize long-read error patterns and simulate them, have been developed. However, there is still room for improvement in the simulation of the non-uniformity of errors. RESULTS: To capture characteristics of errors in reads for long-read sequencers, here, we introduce a generative model for quality scores, in which a hidden Markov Model with a latest model selection method, called factorized information criteria, is utilized. We evaluated our developed simulator from various points, indicating that our simulator successfully simulates reads that are consistent with real reads. AVAILABILITY AND IMPLEMENTATION: The source codes of PBSIM2 are freely available from https://github.com/yukiteruono/pbsim2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8097687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-80976872021-05-10 PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores Ono, Yukiteru Asai, Kiyoshi Hamada, Michiaki Bioinformatics Original Papers MOTIVATION: Recent advances in high-throughput long-read sequencers, such as PacBio and Oxford Nanopore sequencers, produce longer reads with more errors than short-read sequencers. In addition to the high error rates of reads, non-uniformity of errors leads to difficulties in various downstream analyses using long reads. Many useful simulators, which characterize long-read error patterns and simulate them, have been developed. However, there is still room for improvement in the simulation of the non-uniformity of errors. RESULTS: To capture characteristics of errors in reads for long-read sequencers, here, we introduce a generative model for quality scores, in which a hidden Markov Model with a latest model selection method, called factorized information criteria, is utilized. We evaluated our developed simulator from various points, indicating that our simulator successfully simulates reads that are consistent with real reads. AVAILABILITY AND IMPLEMENTATION: The source codes of PBSIM2 are freely available from https://github.com/yukiteruono/pbsim2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-09-25 /pmc/articles/PMC8097687/ /pubmed/32976553 http://dx.doi.org/10.1093/bioinformatics/btaa835 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Papers Ono, Yukiteru Asai, Kiyoshi Hamada, Michiaki PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores |
title | PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores |
title_full | PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores |
title_fullStr | PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores |
title_full_unstemmed | PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores |
title_short | PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores |
title_sort | pbsim2: a simulator for long-read sequencers with a novel generative model of quality scores |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097687/ https://www.ncbi.nlm.nih.gov/pubmed/32976553 http://dx.doi.org/10.1093/bioinformatics/btaa835 |
work_keys_str_mv | AT onoyukiteru pbsim2asimulatorforlongreadsequencerswithanovelgenerativemodelofqualityscores AT asaikiyoshi pbsim2asimulatorforlongreadsequencerswithanovelgenerativemodelofqualityscores AT hamadamichiaki pbsim2asimulatorforlongreadsequencerswithanovelgenerativemodelofqualityscores |