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Alternative splicing analysis benchmark with DICAST
Alternative splicing is a major contributor to transcriptome and proteome diversity in health and disease. A plethora of tools have been developed for studying alternative splicing in RNA-seq data. Previous benchmarks focused on isoform quantification and mapping. They neglected event detection tool...
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/PMC10227362/ https://www.ncbi.nlm.nih.gov/pubmed/37260511 http://dx.doi.org/10.1093/nargab/lqad044 |
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author | Fenn, Amit Tsoy, Olga Faro, Tim Rößler, Fanny L M Dietrich, Alexander Kersting, Johannes Louadi, Zakaria Lio, Chit Tong Völker, Uwe Baumbach, Jan Kacprowski, Tim List, Markus |
author_facet | Fenn, Amit Tsoy, Olga Faro, Tim Rößler, Fanny L M Dietrich, Alexander Kersting, Johannes Louadi, Zakaria Lio, Chit Tong Völker, Uwe Baumbach, Jan Kacprowski, Tim List, Markus |
author_sort | Fenn, Amit |
collection | PubMed |
description | Alternative splicing is a major contributor to transcriptome and proteome diversity in health and disease. A plethora of tools have been developed for studying alternative splicing in RNA-seq data. Previous benchmarks focused on isoform quantification and mapping. They neglected event detection tools, which arguably provide the most detailed insights into the alternative splicing process. DICAST offers a modular and extensible framework for analysing alternative splicing integrating eleven splice-aware mapping and eight event detection tools. We benchmark all tools extensively on simulated as well as whole blood RNA-seq data. STAR and HISAT2 demonstrated the best balance between performance and run time. The performance of event detection tools varies widely with no tool outperforming all others. DICAST allows researchers to employ a consensus approach to consider the most successful tools jointly for robust event detection. Furthermore, we propose the first reporting standard to unify existing formats and to guide future tool development. |
format | Online Article Text |
id | pubmed-10227362 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-102273622023-05-31 Alternative splicing analysis benchmark with DICAST Fenn, Amit Tsoy, Olga Faro, Tim Rößler, Fanny L M Dietrich, Alexander Kersting, Johannes Louadi, Zakaria Lio, Chit Tong Völker, Uwe Baumbach, Jan Kacprowski, Tim List, Markus NAR Genom Bioinform Methods and Benchmark Surveys Alternative splicing is a major contributor to transcriptome and proteome diversity in health and disease. A plethora of tools have been developed for studying alternative splicing in RNA-seq data. Previous benchmarks focused on isoform quantification and mapping. They neglected event detection tools, which arguably provide the most detailed insights into the alternative splicing process. DICAST offers a modular and extensible framework for analysing alternative splicing integrating eleven splice-aware mapping and eight event detection tools. We benchmark all tools extensively on simulated as well as whole blood RNA-seq data. STAR and HISAT2 demonstrated the best balance between performance and run time. The performance of event detection tools varies widely with no tool outperforming all others. DICAST allows researchers to employ a consensus approach to consider the most successful tools jointly for robust event detection. Furthermore, we propose the first reporting standard to unify existing formats and to guide future tool development. Oxford University Press 2023-05-30 /pmc/articles/PMC10227362/ /pubmed/37260511 http://dx.doi.org/10.1093/nargab/lqad044 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. 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 | Methods and Benchmark Surveys Fenn, Amit Tsoy, Olga Faro, Tim Rößler, Fanny L M Dietrich, Alexander Kersting, Johannes Louadi, Zakaria Lio, Chit Tong Völker, Uwe Baumbach, Jan Kacprowski, Tim List, Markus Alternative splicing analysis benchmark with DICAST |
title | Alternative splicing analysis benchmark with DICAST |
title_full | Alternative splicing analysis benchmark with DICAST |
title_fullStr | Alternative splicing analysis benchmark with DICAST |
title_full_unstemmed | Alternative splicing analysis benchmark with DICAST |
title_short | Alternative splicing analysis benchmark with DICAST |
title_sort | alternative splicing analysis benchmark with dicast |
topic | Methods and Benchmark Surveys |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10227362/ https://www.ncbi.nlm.nih.gov/pubmed/37260511 http://dx.doi.org/10.1093/nargab/lqad044 |
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