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NanoPack2: population-scale evaluation of long-read sequencing data
SUMMARY: Increases in the cohort size in long-read sequencing projects necessitate more efficient software for quality assessment and processing of sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. Here, we describe novel tools for summarizing experiments, filtering datasets...
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/PMC10196664/ https://www.ncbi.nlm.nih.gov/pubmed/37171891 http://dx.doi.org/10.1093/bioinformatics/btad311 |
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author | De Coster, Wouter Rademakers, Rosa |
author_facet | De Coster, Wouter Rademakers, Rosa |
author_sort | De Coster, Wouter |
collection | PubMed |
description | SUMMARY: Increases in the cohort size in long-read sequencing projects necessitate more efficient software for quality assessment and processing of sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. Here, we describe novel tools for summarizing experiments, filtering datasets, visualizing phased alignments results, and updates to the NanoPack software suite. AVAILABILITY AND IMPLEMENTATION: The cramino, chopper, kyber, and phasius tools are written in Rust and available as executable binaries without requiring installation or managing dependencies. Binaries build on musl are available for broad compatibility. NanoPlot and NanoComp are written in Python3. Links to the separate tools and their documentation can be found at https://github.com/wdecoster/nanopack. All tools are compatible with Linux, Mac OS, and the MS Windows Subsystem for Linux and are released under the MIT license. The repositories include test data, and the tools are continuously tested using GitHub Actions and can be installed with the conda dependency manager. |
format | Online Article Text |
id | pubmed-10196664 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-101966642023-05-20 NanoPack2: population-scale evaluation of long-read sequencing data De Coster, Wouter Rademakers, Rosa Bioinformatics Applications Note SUMMARY: Increases in the cohort size in long-read sequencing projects necessitate more efficient software for quality assessment and processing of sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. Here, we describe novel tools for summarizing experiments, filtering datasets, visualizing phased alignments results, and updates to the NanoPack software suite. AVAILABILITY AND IMPLEMENTATION: The cramino, chopper, kyber, and phasius tools are written in Rust and available as executable binaries without requiring installation or managing dependencies. Binaries build on musl are available for broad compatibility. NanoPlot and NanoComp are written in Python3. Links to the separate tools and their documentation can be found at https://github.com/wdecoster/nanopack. All tools are compatible with Linux, Mac OS, and the MS Windows Subsystem for Linux and are released under the MIT license. The repositories include test data, and the tools are continuously tested using GitHub Actions and can be installed with the conda dependency manager. Oxford University Press 2023-05-12 /pmc/articles/PMC10196664/ /pubmed/37171891 http://dx.doi.org/10.1093/bioinformatics/btad311 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 De Coster, Wouter Rademakers, Rosa NanoPack2: population-scale evaluation of long-read sequencing data |
title | NanoPack2: population-scale evaluation of long-read sequencing data |
title_full | NanoPack2: population-scale evaluation of long-read sequencing data |
title_fullStr | NanoPack2: population-scale evaluation of long-read sequencing data |
title_full_unstemmed | NanoPack2: population-scale evaluation of long-read sequencing data |
title_short | NanoPack2: population-scale evaluation of long-read sequencing data |
title_sort | nanopack2: population-scale evaluation of long-read sequencing data |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196664/ https://www.ncbi.nlm.nih.gov/pubmed/37171891 http://dx.doi.org/10.1093/bioinformatics/btad311 |
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