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.
Klemm, P., Frommolt, P., & Kornfeld, J. W. (2019). S ·nr: A visual analytics framework for contextual analyses of private and public RNA-seq data. BMC Genomics, 20(1). https://doi.org/10.1186/s12864-018-5396-0