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Grape RNA-Seq analysis pipeline environment

Motivation: The avalanche of data arriving since the development of NGS technologies have prompted the need for developing fast, accurate and easily automated bioinformatic tools capable of dealing with massive datasets. Among the most productive applications of NGS technologies is the sequencing of...

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Autores principales: Knowles, David G., Röder, Maik, Merkel, Angelika, Guigó, Roderic
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3582270/
https://www.ncbi.nlm.nih.gov/pubmed/23329413
http://dx.doi.org/10.1093/bioinformatics/btt016
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author Knowles, David G.
Röder, Maik
Merkel, Angelika
Guigó, Roderic
author_facet Knowles, David G.
Röder, Maik
Merkel, Angelika
Guigó, Roderic
author_sort Knowles, David G.
collection PubMed
description Motivation: The avalanche of data arriving since the development of NGS technologies have prompted the need for developing fast, accurate and easily automated bioinformatic tools capable of dealing with massive datasets. Among the most productive applications of NGS technologies is the sequencing of cellular RNA, known as RNA-Seq. Although RNA-Seq provides similar or superior dynamic range than microarrays at similar or lower cost, the lack of standard and user-friendly pipelines is a bottleneck preventing RNA-Seq from becoming the standard for transcriptome analysis. Results: In this work we present a pipeline for processing and analyzing RNA-Seq data, that we have named Grape (Grape RNA-Seq Analysis Pipeline Environment). Grape supports raw sequencing reads produced by a variety of technologies, either in FASTA or FASTQ format, or as prealigned reads in SAM/BAM format. A minimal Grape configuration consists of the file location of the raw sequencing reads, the genome of the species and the corresponding gene and transcript annotation. Grape first runs a set of quality control steps, and then aligns the reads to the genome, a step that is omitted for prealigned read formats. Grape next estimates gene and transcript expression levels, calculates exon inclusion levels and identifies novel transcripts. Grape can be run on a single computer or in parallel on a computer cluster. It is distributed with specific mapping and quantification tools, but given its modular design, any tool supporting popular data interchange formats can be integrated. Availability: Grape can be obtained from the Bioinformatics and Genomics website at: http://big.crg.cat/services/grape. Contact: david.gonzalez@crg.eu or roderic.guigo@crg.eu
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spelling pubmed-35822702013-02-26 Grape RNA-Seq analysis pipeline environment Knowles, David G. Röder, Maik Merkel, Angelika Guigó, Roderic Bioinformatics Original Papers Motivation: The avalanche of data arriving since the development of NGS technologies have prompted the need for developing fast, accurate and easily automated bioinformatic tools capable of dealing with massive datasets. Among the most productive applications of NGS technologies is the sequencing of cellular RNA, known as RNA-Seq. Although RNA-Seq provides similar or superior dynamic range than microarrays at similar or lower cost, the lack of standard and user-friendly pipelines is a bottleneck preventing RNA-Seq from becoming the standard for transcriptome analysis. Results: In this work we present a pipeline for processing and analyzing RNA-Seq data, that we have named Grape (Grape RNA-Seq Analysis Pipeline Environment). Grape supports raw sequencing reads produced by a variety of technologies, either in FASTA or FASTQ format, or as prealigned reads in SAM/BAM format. A minimal Grape configuration consists of the file location of the raw sequencing reads, the genome of the species and the corresponding gene and transcript annotation. Grape first runs a set of quality control steps, and then aligns the reads to the genome, a step that is omitted for prealigned read formats. Grape next estimates gene and transcript expression levels, calculates exon inclusion levels and identifies novel transcripts. Grape can be run on a single computer or in parallel on a computer cluster. It is distributed with specific mapping and quantification tools, but given its modular design, any tool supporting popular data interchange formats can be integrated. Availability: Grape can be obtained from the Bioinformatics and Genomics website at: http://big.crg.cat/services/grape. Contact: david.gonzalez@crg.eu or roderic.guigo@crg.eu Oxford University Press 2013-03-01 2013-01-17 /pmc/articles/PMC3582270/ /pubmed/23329413 http://dx.doi.org/10.1093/bioinformatics/btt016 Text en © The Author 2013. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Knowles, David G.
Röder, Maik
Merkel, Angelika
Guigó, Roderic
Grape RNA-Seq analysis pipeline environment
title Grape RNA-Seq analysis pipeline environment
title_full Grape RNA-Seq analysis pipeline environment
title_fullStr Grape RNA-Seq analysis pipeline environment
title_full_unstemmed Grape RNA-Seq analysis pipeline environment
title_short Grape RNA-Seq analysis pipeline environment
title_sort grape rna-seq analysis pipeline environment
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3582270/
https://www.ncbi.nlm.nih.gov/pubmed/23329413
http://dx.doi.org/10.1093/bioinformatics/btt016
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