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Augmenting transcriptome assembly by combining de novo and genome-guided tools

Researchers interested in studying and constructing transcriptomes, especially for non-model species, face the conundrum of choosing from a number of available de novo and genome-guided assemblers. None of the popular assembly tools in use today achieve requisite sensitivity, specificity or recovery...

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Detalles Bibliográficos
Autores principales: Jain, Prachi, Krishnan, Neeraja M., Panda, Binay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3746961/
https://www.ncbi.nlm.nih.gov/pubmed/24024083
http://dx.doi.org/10.7717/peerj.133
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author Jain, Prachi
Krishnan, Neeraja M.
Panda, Binay
author_facet Jain, Prachi
Krishnan, Neeraja M.
Panda, Binay
author_sort Jain, Prachi
collection PubMed
description Researchers interested in studying and constructing transcriptomes, especially for non-model species, face the conundrum of choosing from a number of available de novo and genome-guided assemblers. None of the popular assembly tools in use today achieve requisite sensitivity, specificity or recovery of full-length transcripts on their own. Here, we present a comprehensive comparative study of the performance of various assemblers. Additionally, we present an approach to combinatorially augment transciptome assembly by using both de novo and genome-guided tools. In our study, we obtained the best recovery and most full-length transcripts with Trinity and TopHat1-Cufflinks, respectively. The sensitivity of the assembly and isoform recovery was superior, without compromising much on the specificity, when transcripts from Trinity were augmented with those from TopHat1-Cufflinks.
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spelling pubmed-37469612013-09-10 Augmenting transcriptome assembly by combining de novo and genome-guided tools Jain, Prachi Krishnan, Neeraja M. Panda, Binay PeerJ Bioinformatics Researchers interested in studying and constructing transcriptomes, especially for non-model species, face the conundrum of choosing from a number of available de novo and genome-guided assemblers. None of the popular assembly tools in use today achieve requisite sensitivity, specificity or recovery of full-length transcripts on their own. Here, we present a comprehensive comparative study of the performance of various assemblers. Additionally, we present an approach to combinatorially augment transciptome assembly by using both de novo and genome-guided tools. In our study, we obtained the best recovery and most full-length transcripts with Trinity and TopHat1-Cufflinks, respectively. The sensitivity of the assembly and isoform recovery was superior, without compromising much on the specificity, when transcripts from Trinity were augmented with those from TopHat1-Cufflinks. PeerJ Inc. 2013-08-15 /pmc/articles/PMC3746961/ /pubmed/24024083 http://dx.doi.org/10.7717/peerj.133 Text en © 2013 Jain et al. http://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Bioinformatics
Jain, Prachi
Krishnan, Neeraja M.
Panda, Binay
Augmenting transcriptome assembly by combining de novo and genome-guided tools
title Augmenting transcriptome assembly by combining de novo and genome-guided tools
title_full Augmenting transcriptome assembly by combining de novo and genome-guided tools
title_fullStr Augmenting transcriptome assembly by combining de novo and genome-guided tools
title_full_unstemmed Augmenting transcriptome assembly by combining de novo and genome-guided tools
title_short Augmenting transcriptome assembly by combining de novo and genome-guided tools
title_sort augmenting transcriptome assembly by combining de novo and genome-guided tools
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3746961/
https://www.ncbi.nlm.nih.gov/pubmed/24024083
http://dx.doi.org/10.7717/peerj.133
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