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Limitations of alignment-free tools in total RNA-seq quantification
BACKGROUND: Alignment-free RNA quantification tools have significantly increased the speed of RNA-seq analysis. However, it is unclear whether these state-of-the-art RNA-seq analysis pipelines can quantify small RNAs as accurately as they do with long RNAs in the context of total RNA quantification....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042521/ https://www.ncbi.nlm.nih.gov/pubmed/29969991 http://dx.doi.org/10.1186/s12864-018-4869-5 |
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author | Wu, Douglas C. Yao, Jun Ho, Kevin S. Lambowitz, Alan M. Wilke, Claus O. |
author_facet | Wu, Douglas C. Yao, Jun Ho, Kevin S. Lambowitz, Alan M. Wilke, Claus O. |
author_sort | Wu, Douglas C. |
collection | PubMed |
description | BACKGROUND: Alignment-free RNA quantification tools have significantly increased the speed of RNA-seq analysis. However, it is unclear whether these state-of-the-art RNA-seq analysis pipelines can quantify small RNAs as accurately as they do with long RNAs in the context of total RNA quantification. RESULT: We comprehensively tested and compared four RNA-seq pipelines for accuracy of gene quantification and fold-change estimation. We used a novel total RNA benchmarking dataset in which small non-coding RNAs are highly represented along with other long RNAs. The four RNA-seq pipelines consisted of two commonly-used alignment-free pipelines and two variants of alignment-based pipelines. We found that all pipelines showed high accuracy for quantifying the expression of long and highly-abundant genes. However, alignment-free pipelines showed systematically poorer performance in quantifying lowly-abundant and small RNAs. CONCLUSION: We have shown that alignment-free and traditional alignment-based quantification methods perform similarly for common gene targets, such as protein-coding genes. However, we have identified a potential pitfall in analyzing and quantifying lowly-expressed genes and small RNAs with alignment-free pipelines, especially when these small RNAs contain biological variations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-4869-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6042521 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60425212018-07-13 Limitations of alignment-free tools in total RNA-seq quantification Wu, Douglas C. Yao, Jun Ho, Kevin S. Lambowitz, Alan M. Wilke, Claus O. BMC Genomics Research Article BACKGROUND: Alignment-free RNA quantification tools have significantly increased the speed of RNA-seq analysis. However, it is unclear whether these state-of-the-art RNA-seq analysis pipelines can quantify small RNAs as accurately as they do with long RNAs in the context of total RNA quantification. RESULT: We comprehensively tested and compared four RNA-seq pipelines for accuracy of gene quantification and fold-change estimation. We used a novel total RNA benchmarking dataset in which small non-coding RNAs are highly represented along with other long RNAs. The four RNA-seq pipelines consisted of two commonly-used alignment-free pipelines and two variants of alignment-based pipelines. We found that all pipelines showed high accuracy for quantifying the expression of long and highly-abundant genes. However, alignment-free pipelines showed systematically poorer performance in quantifying lowly-abundant and small RNAs. CONCLUSION: We have shown that alignment-free and traditional alignment-based quantification methods perform similarly for common gene targets, such as protein-coding genes. However, we have identified a potential pitfall in analyzing and quantifying lowly-expressed genes and small RNAs with alignment-free pipelines, especially when these small RNAs contain biological variations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-4869-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-03 /pmc/articles/PMC6042521/ /pubmed/29969991 http://dx.doi.org/10.1186/s12864-018-4869-5 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Wu, Douglas C. Yao, Jun Ho, Kevin S. Lambowitz, Alan M. Wilke, Claus O. Limitations of alignment-free tools in total RNA-seq quantification |
title | Limitations of alignment-free tools in total RNA-seq quantification |
title_full | Limitations of alignment-free tools in total RNA-seq quantification |
title_fullStr | Limitations of alignment-free tools in total RNA-seq quantification |
title_full_unstemmed | Limitations of alignment-free tools in total RNA-seq quantification |
title_short | Limitations of alignment-free tools in total RNA-seq quantification |
title_sort | limitations of alignment-free tools in total rna-seq quantification |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042521/ https://www.ncbi.nlm.nih.gov/pubmed/29969991 http://dx.doi.org/10.1186/s12864-018-4869-5 |
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