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PerSVade: personalized structural variant detection in any species of interest
Structural variants (SVs) underlie genomic variation but are often overlooked due to difficult detection from short reads. Most algorithms have been tested on humans, and it remains unclear how applicable they are in other organisms. To solve this, we develop perSVade (personalized structural variat...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9380391/ https://www.ncbi.nlm.nih.gov/pubmed/35974382 http://dx.doi.org/10.1186/s13059-022-02737-4 |
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author | Schikora-Tamarit, Miquel Àngel Gabaldón, Toni |
author_facet | Schikora-Tamarit, Miquel Àngel Gabaldón, Toni |
author_sort | Schikora-Tamarit, Miquel Àngel |
collection | PubMed |
description | Structural variants (SVs) underlie genomic variation but are often overlooked due to difficult detection from short reads. Most algorithms have been tested on humans, and it remains unclear how applicable they are in other organisms. To solve this, we develop perSVade (personalized structural variation detection), a sample-tailored pipeline that provides optimally called SVs and their inferred accuracy, as well as small and copy number variants. PerSVade increases SV calling accuracy on a benchmark of six eukaryotes. We find no universal set of optimal parameters, underscoring the need for sample-specific parameter optimization. PerSVade will facilitate SV detection and study across diverse organisms. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02737-4. |
format | Online Article Text |
id | pubmed-9380391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93803912022-08-17 PerSVade: personalized structural variant detection in any species of interest Schikora-Tamarit, Miquel Àngel Gabaldón, Toni Genome Biol Software Structural variants (SVs) underlie genomic variation but are often overlooked due to difficult detection from short reads. Most algorithms have been tested on humans, and it remains unclear how applicable they are in other organisms. To solve this, we develop perSVade (personalized structural variation detection), a sample-tailored pipeline that provides optimally called SVs and their inferred accuracy, as well as small and copy number variants. PerSVade increases SV calling accuracy on a benchmark of six eukaryotes. We find no universal set of optimal parameters, underscoring the need for sample-specific parameter optimization. PerSVade will facilitate SV detection and study across diverse organisms. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02737-4. BioMed Central 2022-08-16 /pmc/articles/PMC9380391/ /pubmed/35974382 http://dx.doi.org/10.1186/s13059-022-02737-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 | Software Schikora-Tamarit, Miquel Àngel Gabaldón, Toni PerSVade: personalized structural variant detection in any species of interest |
title | PerSVade: personalized structural variant detection in any species of interest |
title_full | PerSVade: personalized structural variant detection in any species of interest |
title_fullStr | PerSVade: personalized structural variant detection in any species of interest |
title_full_unstemmed | PerSVade: personalized structural variant detection in any species of interest |
title_short | PerSVade: personalized structural variant detection in any species of interest |
title_sort | persvade: personalized structural variant detection in any species of interest |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9380391/ https://www.ncbi.nlm.nih.gov/pubmed/35974382 http://dx.doi.org/10.1186/s13059-022-02737-4 |
work_keys_str_mv | AT schikoratamaritmiquelangel persvadepersonalizedstructuralvariantdetectioninanyspeciesofinterest AT gabaldontoni persvadepersonalizedstructuralvariantdetectioninanyspeciesofinterest |