Open Accesss·nr: a visual analytics framework for contextual analyses of private and public RNA-seq data
Author(s) -
Paul Klemm,
Peter Frommolt,
Jan-Wilhelm Kornfeld
Publication year - 2019
Publication title -
bmc genomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.547
H-Index - 167
ISSN - 1471-2164
DOI - 10.1186/s12864-018-5396-0
Subject(s) - computer science , context (archaeology) , visual analytics , data science , data analysis , computational biology , rna seq , visualization , biology , data mining , gene expression , gene , transcriptome , genetics , paleontology
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.