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Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools

One of the key applications of next-generation sequencing (NGS) technologies is RNA-Seq for transcriptome genome-wide analysis. Although multiple studies have evaluated and benchmarked RNA-Seq tools dedicated to gene level analysis, few studies have assessed their effectiveness on the transcript-iso...

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Autores principales: Leshkowitz, Dena, Feldmesser, Ester, Friedlander, Gilgi, Jona, Ghil, Ainbinder, Elena, Parmet, Yisrael, Horn-Saban, Shirley
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4839710/
https://www.ncbi.nlm.nih.gov/pubmed/27100792
http://dx.doi.org/10.1371/journal.pone.0153782
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author Leshkowitz, Dena
Feldmesser, Ester
Friedlander, Gilgi
Jona, Ghil
Ainbinder, Elena
Parmet, Yisrael
Horn-Saban, Shirley
author_facet Leshkowitz, Dena
Feldmesser, Ester
Friedlander, Gilgi
Jona, Ghil
Ainbinder, Elena
Parmet, Yisrael
Horn-Saban, Shirley
author_sort Leshkowitz, Dena
collection PubMed
description One of the key applications of next-generation sequencing (NGS) technologies is RNA-Seq for transcriptome genome-wide analysis. Although multiple studies have evaluated and benchmarked RNA-Seq tools dedicated to gene level analysis, few studies have assessed their effectiveness on the transcript-isoform level. Alternative splicing is a naturally occurring phenomenon in eukaryotes, significantly increasing the biodiversity of proteins that can be encoded by the genome. The aim of this study was to assess and compare the ability of the bioinformatics approaches and tools to assemble, quantify and detect differentially expressed transcripts using RNA-Seq data, in a controlled experiment. To this end, in vitro synthesized mouse spike-in control transcripts were added to the total RNA of differentiating mouse embryonic bodies, and their expression patterns were measured. This novel approach was used to assess the accuracy of the tools, as established by comparing the observed results versus the results expected of the mouse controlled spiked-in transcripts. We found that detection of differential expression at the gene level is adequate, yet on the transcript-isoform level, all tools tested lacked accuracy and precision.
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spelling pubmed-48397102016-04-29 Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools Leshkowitz, Dena Feldmesser, Ester Friedlander, Gilgi Jona, Ghil Ainbinder, Elena Parmet, Yisrael Horn-Saban, Shirley PLoS One Research Article One of the key applications of next-generation sequencing (NGS) technologies is RNA-Seq for transcriptome genome-wide analysis. Although multiple studies have evaluated and benchmarked RNA-Seq tools dedicated to gene level analysis, few studies have assessed their effectiveness on the transcript-isoform level. Alternative splicing is a naturally occurring phenomenon in eukaryotes, significantly increasing the biodiversity of proteins that can be encoded by the genome. The aim of this study was to assess and compare the ability of the bioinformatics approaches and tools to assemble, quantify and detect differentially expressed transcripts using RNA-Seq data, in a controlled experiment. To this end, in vitro synthesized mouse spike-in control transcripts were added to the total RNA of differentiating mouse embryonic bodies, and their expression patterns were measured. This novel approach was used to assess the accuracy of the tools, as established by comparing the observed results versus the results expected of the mouse controlled spiked-in transcripts. We found that detection of differential expression at the gene level is adequate, yet on the transcript-isoform level, all tools tested lacked accuracy and precision. Public Library of Science 2016-04-21 /pmc/articles/PMC4839710/ /pubmed/27100792 http://dx.doi.org/10.1371/journal.pone.0153782 Text en © 2016 Leshkowitz et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Leshkowitz, Dena
Feldmesser, Ester
Friedlander, Gilgi
Jona, Ghil
Ainbinder, Elena
Parmet, Yisrael
Horn-Saban, Shirley
Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools
title Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools
title_full Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools
title_fullStr Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools
title_full_unstemmed Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools
title_short Using Synthetic Mouse Spike-In Transcripts to Evaluate RNA-Seq Analysis Tools
title_sort using synthetic mouse spike-in transcripts to evaluate rna-seq analysis tools
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4839710/
https://www.ncbi.nlm.nih.gov/pubmed/27100792
http://dx.doi.org/10.1371/journal.pone.0153782
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