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funcExplorer: a tool for fast data-driven functional characterisation of high-throughput expression data.

Liis Kolberg1, Ivan Kuzmin1, Priit Adler1,2

  • 1Institute of Computer Science, University of Tartu, Juhan Liivi 2, Tartu, Estonia.

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|November 16, 2018
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Summary
This summary is machine-generated.

funcExplorer automates gene expression data analysis by combining clustering and functional enrichment, offering an accessible, reproducible, and visually interactive method for scientists to explore genomic datasets.

Keywords:
Data-drivenFunctional enrichment analysisGene expressionGlobal visualisationHierarchical clusteringMicroarrayProtoarrayRNA-seqfuncExplorer

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput genomic data analysis commonly uses gene expression clustering and functional enrichment.
  • Manual analysis is subjective, lacks reproducibility, and is resource-intensive.
  • Automated pipelines require programming skills and efficient result visualization.

Purpose of the Study:

  • To develop an automated web tool for analyzing high-throughput genomic data.
  • To integrate hierarchical clustering and functional enrichment analysis.
  • To provide an intuitive and visually appealing platform for exploring gene expression patterns.

Main Methods:

  • Developed funcExplorer, a web tool combining hierarchical clustering and enrichment analysis.
  • Utilized structured knowledge from Gene Ontology, KEGG, Reactome, Human Protein Atlas, and Human Phenotype Ontology.
  • Incorporated measures for identifying biologically meaningful clusters and offered data export options.

Main Results:

  • funcExplorer automatically detects functionally related gene clusters.
  • The tool provides a modern graphical user interface with interactive results visualization.
  • Demonstrated comparable performance to manual methods without labor-intensive interference.

Conclusions:

  • funcExplorer offers scientists an open-source web tool for preliminary interactive overviews of genomic data.
  • Enables exploration of expression patterns, gene names, and shared functionalities.
  • Publicly available at https://biit.cs.ut.ee/funcexplorer.