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GeneSCF: a real-time based functional enrichment tool with support for multiple organisms.

Santhilal Subhash1, Chandrasekhar Kanduri2

  • 1Department of Medical Genetics, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, SE-40530, Sweden.

BMC Bioinformatics
|September 14, 2016
PubMed
Summary

GeneSCF is a new command-line tool for real-time functional enrichment analysis of high-throughput data. It uses updated databases for reliable biological interpretation and integrates easily with other analysis pipelines.

Keywords:
Cancer enrichmentFunctional enrichmentsGene OntologyGene enrichment toolKEGGPathway enrichmentsReal-time analysis

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput technologies generate vast datasets requiring functional interpretation.
  • Existing functional enrichment tools need frequent updates to match evolving biological databases.
  • A simplified, real-time analysis tool is needed to interpret gene sets from large-scale studies.

Purpose of the Study:

  • To design a command-line tool, GeneSCF (Gene Set Clustering based on Functional annotations), for real-time functional enrichment analysis.
  • To enable interpretation of biological significance from gene sets using updated functional databases.
  • To provide a user-friendly tool for analyzing data from high-throughput studies.

Main Methods:

  • Developed GeneSCF, a command-line tool for gene set enrichment analysis.
  • Integrated real-time access to prominent functional databases (KEGG, Reactome, Gene Ontology).
  • Tested GeneSCF on Linux systems with minimal dependencies, processing multiple gene lists across organisms.

Main Results:

  • GeneSCF successfully predicted functionally relevant biological information from published datasets.
  • The tool handles data from over 4000 organisms.
  • Core features were validated on Linux machines without complex installation requirements.

Conclusions:

  • GeneSCF offers enhanced reliability through real-time database integration for enrichment analysis.
  • It is easily integrated into existing downstream analysis pipelines.
  • The tool efficiently processes multiple gene lists across different organisms, saving user time.