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s ·nr: a visual analytics framework for contextual analyses of private and public RNA-seq data

BACKGROUND: Next-Generation Sequencing (NGS) has been widely accepted as an essential tool in molecular biology. Reduced costs and automated analysis pipelines make the use of NGS data feasible even for small labs, yet the methods for interpreting the data are not sophisticated enough to account for...

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Autores principales: Klemm, Paul, Frommolt, Peter, Kornfeld, Jan-Wilhelm
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6346532/
https://www.ncbi.nlm.nih.gov/pubmed/30678634
http://dx.doi.org/10.1186/s12864-018-5396-0
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author Klemm, Paul
Frommolt, Peter
Kornfeld, Jan-Wilhelm
author_facet Klemm, Paul
Frommolt, Peter
Kornfeld, Jan-Wilhelm
author_sort Klemm, Paul
collection PubMed
description BACKGROUND: Next-Generation Sequencing (NGS) has been widely accepted as an essential tool in molecular biology. Reduced costs and automated analysis pipelines make the use of NGS data feasible even for small labs, yet the methods for interpreting the data are not sophisticated enough to account for the amount of information. RESULTS: We propose s ·nr, a Visual Analytics tool that provides simple yet powerful visual interfaces for displaying and querying NGS data. It allows researchers to explore their own data in the context of experimental data deposited in public repositories, as well as to extract specific data sets with similar gene expression signatures. We tested s ·nr on 1543 RNA-Seq based mouse differential expression profiles derived from the public ArrayExpress platform. We provide the repository of processed data with this paper. CONCLUSION: s ·nr, easily deployable utilizing its containerized implementation, empowers researchers to analyze and relate their own RNA-Seq as well as to provide interactive and contextual crosstalk with data from public repositories. This allows users to deduce novel and unbiased hypotheses about the underlying molecular processes. DEMO: Login demo/demo: snr.sf.mpg.de (Tested with Google Chrome) ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-5396-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-63465322019-01-29 s ·nr: a visual analytics framework for contextual analyses of private and public RNA-seq data Klemm, Paul Frommolt, Peter Kornfeld, Jan-Wilhelm BMC Genomics Software BACKGROUND: Next-Generation Sequencing (NGS) has been widely accepted as an essential tool in molecular biology. Reduced costs and automated analysis pipelines make the use of NGS data feasible even for small labs, yet the methods for interpreting the data are not sophisticated enough to account for the amount of information. RESULTS: We propose s ·nr, a Visual Analytics tool that provides simple yet powerful visual interfaces for displaying and querying NGS data. It allows researchers to explore their own data in the context of experimental data deposited in public repositories, as well as to extract specific data sets with similar gene expression signatures. We tested s ·nr on 1543 RNA-Seq based mouse differential expression profiles derived from the public ArrayExpress platform. We provide the repository of processed data with this paper. CONCLUSION: s ·nr, easily deployable utilizing its containerized implementation, empowers researchers to analyze and relate their own RNA-Seq as well as to provide interactive and contextual crosstalk with data from public repositories. This allows users to deduce novel and unbiased hypotheses about the underlying molecular processes. DEMO: Login demo/demo: snr.sf.mpg.de (Tested with Google Chrome) ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-5396-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-24 /pmc/articles/PMC6346532/ /pubmed/30678634 http://dx.doi.org/10.1186/s12864-018-5396-0 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Klemm, Paul
Frommolt, Peter
Kornfeld, Jan-Wilhelm
s ·nr: a visual analytics framework for contextual analyses of private and public RNA-seq data
title s ·nr: a visual analytics framework for contextual analyses of private and public RNA-seq data
title_full s ·nr: a visual analytics framework for contextual analyses of private and public RNA-seq data
title_fullStr s ·nr: a visual analytics framework for contextual analyses of private and public RNA-seq data
title_full_unstemmed s ·nr: a visual analytics framework for contextual analyses of private and public RNA-seq data
title_short s ·nr: a visual analytics framework for contextual analyses of private and public RNA-seq data
title_sort s ·nr: a visual analytics framework for contextual analyses of private and public rna-seq data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6346532/
https://www.ncbi.nlm.nih.gov/pubmed/30678634
http://dx.doi.org/10.1186/s12864-018-5396-0
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