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An ‘eFP‐Seq Browser’ for visualizing and exploring RNA sequencing data

SUMMARY: Improvements in next‐generation sequencing technologies have resulted in dramatically reduced sequencing costs. This has led to an explosion of ‘‐seq’‐based methods, of which RNA sequencing (RNA‐seq) for generating transcriptomic data is the most popular. By analysing global patterns of gen...

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Autores principales: Sullivan, Alexander, Purohit, Priyank K., Freese, Nowlan H., Pasha, Asher, Esteban, Eddi, Waese, Jamie, Wu, Alison, Chen, Michelle, Chin, Chih Y., Song, Richard, Watharkar, Sneha R., Chan, Agnes P., Krishnakumar, Vivek, Vaughn, Matthew W., Town, Chris, Loraine, Ann E., Provart, Nicholas J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6899666/
https://www.ncbi.nlm.nih.gov/pubmed/31350781
http://dx.doi.org/10.1111/tpj.14468
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author Sullivan, Alexander
Purohit, Priyank K.
Freese, Nowlan H.
Pasha, Asher
Esteban, Eddi
Waese, Jamie
Wu, Alison
Chen, Michelle
Chin, Chih Y.
Song, Richard
Watharkar, Sneha R.
Chan, Agnes P.
Krishnakumar, Vivek
Vaughn, Matthew W.
Town, Chris
Loraine, Ann E.
Provart, Nicholas J.
author_facet Sullivan, Alexander
Purohit, Priyank K.
Freese, Nowlan H.
Pasha, Asher
Esteban, Eddi
Waese, Jamie
Wu, Alison
Chen, Michelle
Chin, Chih Y.
Song, Richard
Watharkar, Sneha R.
Chan, Agnes P.
Krishnakumar, Vivek
Vaughn, Matthew W.
Town, Chris
Loraine, Ann E.
Provart, Nicholas J.
author_sort Sullivan, Alexander
collection PubMed
description SUMMARY: Improvements in next‐generation sequencing technologies have resulted in dramatically reduced sequencing costs. This has led to an explosion of ‘‐seq’‐based methods, of which RNA sequencing (RNA‐seq) for generating transcriptomic data is the most popular. By analysing global patterns of gene expression in organs/tissues/cells of interest or in response to chemical or environmental perturbations, researchers can better understand an organism's biology. Tools designed to work with large RNA‐seq data sets enable analyses and visualizations to help generate hypotheses about a gene's function. We present here a user‐friendly RNA‐seq data exploration tool, called the ‘eFP‐Seq Browser’, that shows the read map coverage of a gene of interest in each of the samples along with ‘electronic fluorescent pictographic’ (eFP) images that serve as visual representations of expression levels. The tool also summarizes the details of each RNA‐seq experiment, providing links to archival databases and publications. It automatically computes the reads per kilobase per million reads mapped expression‐level summaries and point biserial correlation scores to sort the samples based on a gene's expression level or by how dissimilar the read map profile is from a gene splice variant, to quickly identify samples with the strongest expression level or where alternative splicing might be occurring. Links to the Integrated Genome Browser desktop visualization tool allow researchers to visualize and explore the details of RNA‐seq alignments summarized in eFP‐Seq Browser as coverage graphs. We present four cases of use of the eFP‐Seq Browser for ABI3,SR34,SR45a and U2AF65B, where we examine expression levels and identify alternative splicing. The URL for the browser is https://bar.utoronto.ca/eFP-Seq_Browser/. OPEN RESEARCH BADGES: [Image: see text] This article has earned an Open Data Badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. Tool is at http://sps:urlprefix::https; RNA‐seq data at http://sps:urlprefix::https and http://sps:urlprefix::https. Code is available at http://sps:urlprefix::https
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spelling pubmed-68996662019-12-19 An ‘eFP‐Seq Browser’ for visualizing and exploring RNA sequencing data Sullivan, Alexander Purohit, Priyank K. Freese, Nowlan H. Pasha, Asher Esteban, Eddi Waese, Jamie Wu, Alison Chen, Michelle Chin, Chih Y. Song, Richard Watharkar, Sneha R. Chan, Agnes P. Krishnakumar, Vivek Vaughn, Matthew W. Town, Chris Loraine, Ann E. Provart, Nicholas J. Plant J Resource SUMMARY: Improvements in next‐generation sequencing technologies have resulted in dramatically reduced sequencing costs. This has led to an explosion of ‘‐seq’‐based methods, of which RNA sequencing (RNA‐seq) for generating transcriptomic data is the most popular. By analysing global patterns of gene expression in organs/tissues/cells of interest or in response to chemical or environmental perturbations, researchers can better understand an organism's biology. Tools designed to work with large RNA‐seq data sets enable analyses and visualizations to help generate hypotheses about a gene's function. We present here a user‐friendly RNA‐seq data exploration tool, called the ‘eFP‐Seq Browser’, that shows the read map coverage of a gene of interest in each of the samples along with ‘electronic fluorescent pictographic’ (eFP) images that serve as visual representations of expression levels. The tool also summarizes the details of each RNA‐seq experiment, providing links to archival databases and publications. It automatically computes the reads per kilobase per million reads mapped expression‐level summaries and point biserial correlation scores to sort the samples based on a gene's expression level or by how dissimilar the read map profile is from a gene splice variant, to quickly identify samples with the strongest expression level or where alternative splicing might be occurring. Links to the Integrated Genome Browser desktop visualization tool allow researchers to visualize and explore the details of RNA‐seq alignments summarized in eFP‐Seq Browser as coverage graphs. We present four cases of use of the eFP‐Seq Browser for ABI3,SR34,SR45a and U2AF65B, where we examine expression levels and identify alternative splicing. The URL for the browser is https://bar.utoronto.ca/eFP-Seq_Browser/. OPEN RESEARCH BADGES: [Image: see text] This article has earned an Open Data Badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. Tool is at http://sps:urlprefix::https; RNA‐seq data at http://sps:urlprefix::https and http://sps:urlprefix::https. Code is available at http://sps:urlprefix::https John Wiley and Sons Inc. 2019-08-23 2019-11 /pmc/articles/PMC6899666/ /pubmed/31350781 http://dx.doi.org/10.1111/tpj.14468 Text en © 2019 The Authors The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Resource
Sullivan, Alexander
Purohit, Priyank K.
Freese, Nowlan H.
Pasha, Asher
Esteban, Eddi
Waese, Jamie
Wu, Alison
Chen, Michelle
Chin, Chih Y.
Song, Richard
Watharkar, Sneha R.
Chan, Agnes P.
Krishnakumar, Vivek
Vaughn, Matthew W.
Town, Chris
Loraine, Ann E.
Provart, Nicholas J.
An ‘eFP‐Seq Browser’ for visualizing and exploring RNA sequencing data
title An ‘eFP‐Seq Browser’ for visualizing and exploring RNA sequencing data
title_full An ‘eFP‐Seq Browser’ for visualizing and exploring RNA sequencing data
title_fullStr An ‘eFP‐Seq Browser’ for visualizing and exploring RNA sequencing data
title_full_unstemmed An ‘eFP‐Seq Browser’ for visualizing and exploring RNA sequencing data
title_short An ‘eFP‐Seq Browser’ for visualizing and exploring RNA sequencing data
title_sort ‘efp‐seq browser’ for visualizing and exploring rna sequencing data
topic Resource
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6899666/
https://www.ncbi.nlm.nih.gov/pubmed/31350781
http://dx.doi.org/10.1111/tpj.14468
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