RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing

The ribosome profiling technique (Ribo-seq) allows the selective sequencing of translated RNA regions. Recently, the analysis of genomic sequences associated to Ribo-seq reads has been widely employed to assess their coding potential. These analyses led to the identification of differentially transl...

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Main Authors:	Popa, Alexandra, Lebrigand, Kevin, Paquet, Agnes, Nottet, Nicolas, Robbe-Sermesant, Karine, Waldmann, Rainer, Barbry, Pascal
Format:	Online
Language:	English
Published:	F1000Research 2016
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4918025/

id	pubmed-4918025
recordtype	oai_dc
spelling	pubmed-49180252016-06-23 RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing Popa, Alexandra Lebrigand, Kevin Paquet, Agnes Nottet, Nicolas Robbe-Sermesant, Karine Waldmann, Rainer Barbry, Pascal Software Tool Article The ribosome profiling technique (Ribo-seq) allows the selective sequencing of translated RNA regions. Recently, the analysis of genomic sequences associated to Ribo-seq reads has been widely employed to assess their coding potential. These analyses led to the identification of differentially translated transcripts under different experimental conditions, and/or ribosome pausing on codon motifs. In the context of the ever-growing need for tools analyzing Ribo-seq reads, we have developed ‘RiboProfiling’, a new Bioconductor open-source package. ‘RiboProfiling’ provides a full pipeline to cover all key steps for the analysis of ribosome footprints. This pipeline has been implemented in a single R workflow. The package takes an alignment (BAM) file as input and performs ribosome footprint quantification at a transcript level. It also identifies footprint accumulation on particular amino acids or multi amino-acids motifs. Report summary graphs and data quantification are generated automatically. The package facilitates quality assessment and quantification of Ribo-seq experiments. Its implementation in Bioconductor enables the modeling and statistical analysis of its output through the vast choice of packages available in R. This article illustrates how to identify codon-motifs accumulating ribosome footprints, based on data from Escherichia coli. F1000Research 2016-06-09 /pmc/articles/PMC4918025/ /pubmed/27347386 http://dx.doi.org/10.12688/f1000research.8964.1 Text en Copyright: © 2016 Popa A et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Popa, Alexandra Lebrigand, Kevin Paquet, Agnes Nottet, Nicolas Robbe-Sermesant, Karine Waldmann, Rainer Barbry, Pascal
spellingShingle	Popa, Alexandra Lebrigand, Kevin Paquet, Agnes Nottet, Nicolas Robbe-Sermesant, Karine Waldmann, Rainer Barbry, Pascal RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing
author_facet	Popa, Alexandra Lebrigand, Kevin Paquet, Agnes Nottet, Nicolas Robbe-Sermesant, Karine Waldmann, Rainer Barbry, Pascal
author_sort	Popa, Alexandra
title	RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing
title_short	RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing
title_full	RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing
title_fullStr	RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing
title_full_unstemmed	RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing
title_sort	riboprofiling: a bioconductor package for standard ribo-seq pipeline processing
description	The ribosome profiling technique (Ribo-seq) allows the selective sequencing of translated RNA regions. Recently, the analysis of genomic sequences associated to Ribo-seq reads has been widely employed to assess their coding potential. These analyses led to the identification of differentially translated transcripts under different experimental conditions, and/or ribosome pausing on codon motifs. In the context of the ever-growing need for tools analyzing Ribo-seq reads, we have developed ‘RiboProfiling’, a new Bioconductor open-source package. ‘RiboProfiling’ provides a full pipeline to cover all key steps for the analysis of ribosome footprints. This pipeline has been implemented in a single R workflow. The package takes an alignment (BAM) file as input and performs ribosome footprint quantification at a transcript level. It also identifies footprint accumulation on particular amino acids or multi amino-acids motifs. Report summary graphs and data quantification are generated automatically. The package facilitates quality assessment and quantification of Ribo-seq experiments. Its implementation in Bioconductor enables the modeling and statistical analysis of its output through the vast choice of packages available in R. This article illustrates how to identify codon-motifs accumulating ribosome footprints, based on data from Escherichia coli.
publisher	F1000Research
publishDate	2016
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4918025/
_version_	1613598575547121664

RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processing

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