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GTB - an online genome tolerance browser.

Hashem A Shihab1, Mark F Rogers2, Michael Ferlaino2

  • 1MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, BS8 2BN, UK.

BMC Bioinformatics
|January 8, 2017
PubMed
Summary

The Genome Tolerance Browser visualizes mutation impact predictions from multiple algorithms, aiding in identifying genomic regions of interest. This tool helps researchers understand and compare different single nucleotide variant prediction methods.

Keywords:
Genome browserGenome toleranceMutationPathogenicity predictionPrediction algorithmSNVsVariant effect prediction

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Accurate prediction of single nucleotide variant (SNV) impact is crucial for genomic research.
  • Numerous in silico algorithms exist for SNV identification and prioritization.
  • A gap exists in tools for visualizing genome-wide mutation tolerance and comparing prediction algorithms.

Purpose of the Study:

  • To introduce the Genome Tolerance Browser (GTB) as a novel online tool.
  • To provide a platform for visualizing predicted genomic mutation tolerance.
  • To enable comparison of various in silico prediction algorithms.

Main Methods:

  • Developed an online genome browser, the Genome Tolerance Browser (GTB).
  • Integrated multiple in silico prediction algorithms and conservation scores.
  • Included 13 genome-wide, 12 non-synonymous, and 4 cancer-specific algorithms.

Main Results:

  • The GTB visualizes predicted genome-wide mutation tolerance.
  • It summarizes data from numerous prediction algorithms and conservation scores.
  • The browser facilitates comparison of different SNV prediction methods.

Conclusions:

  • The GTB allows visualization of similarities and differences between prediction algorithms.
  • Users can upload custom data as additional tracks for integrated analysis.
  • Facilitates rapid identification of potential genomic regions of interest.