GeMSE

GenoMetric Space Explorer (GeMSE) is a tool for exploring, analyzing, and visualizing NGS (Next-Generation Sequencing) processed data. As public repositories of NGS-processed data continue to grow, the need for user-friendly and effective data exploration, analysis, and visualization tools is becoming increasingly relevant. GeMSE provides interactive analytics, on-the-fly integration of analysis and visualization phases, and seamless "sense-making" of data. GeMSE was designed to meet the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can be used to start analyzing data from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions. Additionally, metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis, and visualization that help biologists and bioinformaticians make sense of heterogeneous genomic datasets. The tool provides explorative interaction support, which enables users to trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps.

Topic

Genomics;Data visualisation;Sequencing;Phylogenetics;Gene expression

Detail

  • Operation: Phylogenetic tree visualisation;Expression data visualisation

  • Software interface: Graphical user interface

  • Language: R;Java

  • License: GNU General Public License v3

  • Cost: Free

  • Version name: 2.0.3

  • Credit: The Advanced ERC Grant “Data-Driven Genomic Computing (GeCo)” project, funded by the European Research Council.

  • Input: BED, BroadPeak, NarrowPeak, GTF, general tab-delimited

  • Output: -

  • Contact: vahid.jalili@polimi.it

  • Collection: -

  • Maturity: Stable

Publications

  • Explorative visual analytics on interval-based genomic data and their metadata.
  • Jalili V, et al. Explorative visual analytics on interval-based genomic data and their metadata. Explorative visual analytics on interval-based genomic data and their metadata. 2017; 18:536. doi: 10.1186/s12859-017-1945-9
  • https://doi.org/10.1186/s12859-017-1945-9
  • PMID: 29202689
  • PMC: PMC5715631

Download and documentation


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