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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....

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Autores principales: Wu, Douglas C., Yao, Jun, Ho, Kevin S., Lambowitz, Alan M., Wilke, Claus O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
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.
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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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