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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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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. |
format | Online Article Text |
id | pubmed-6346532 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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