GTB – An Online Genome Tolerance Browser

Hashem Shihab, Mark Rogers, Michael Ferlaino, Colin Campbell, Tom Gaunt

Research output: Contribution to journalArticle (Academic Journal)peer-review

3 Citations (Scopus)
260 Downloads (Pure)

Abstract

Background: Accurate methods capable of predicting the impact of single nucleotide variants (SNVs) are assuming ever increasing importance. There exists a plethora of in silico algorithms designed to help identify and prioritize SNVs across the human genome for further investigation. However, no tool exists to visualize the predicted tolerance of the genome to mutation, or the similarities between these methods.
Results: We present the Genome Tolerance Browser (GTB): an online genome browser for visualizing the predicted tolerance of the genome to mutation. The server summarizes several in silico prediction algorithms and conservation scores: including 13 genome-wide prediction algorithms and conservation scores, 12 non-synonymous prediction algorithms and 4 cancerspecific algorithms.
Conclusion: The GTB enables users to visualize the similarities and differences between several prediction algorithms and to upload their own data as additional tracks; thereby facilitating the rapid identification of potential regions of interest.
Original languageEnglish
Number of pages6
JournalBMC Bioinformatics
Volume18
Issue number20
DOIs
Publication statusPublished - 6 Jan 2017

Keywords

  • SNVs
  • Mutation
  • Pathogenicity Prediction
  • Prediction Algorithm
  • Variant Effect Prediction
  • Genome Browser
  • Genome Tolerance

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