SVI: A simple single-nucleotide human variant interpretation tool for clinical use

Paolo Missier*, Eldarina Wijaya, Ryan Kirby, Michael Keogh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The rapid evolution of Next Generation Sequencing technology will soon make it possible to test patients for genetic disorders at population scale. However, clinical interpretation of human variants extracted from raw NGS data in the clinical setting is likely to become a bottleneck, as long as it requires expert human judgement. While several attempts are under way to try and automate the diagnostic process, most still assume a specialist’s understanding of the variants’ significance. In this paper we present our early experiments with a simple process and prototype clinical tool for single-nucleotide variant filtering, called SVI, which automates much of the interpretation process by integrating disease-gene and disease-variant mapping resources. As the content and quality of these resources improve over time, it is important to identify past patients’ cases which may benefit from re-analysis. By persistently recording the entire diagnostic process, SVI can selectively trigger case re-analysis on the basis of updates in the external knowledge sources.

Original languageEnglish
Title of host publicationData Integration in the Life Sciences - 11th International Conference, DILS 2015, Proceedings
EditorsJose-Luis Ambite, Ashish N. Naveen
PublisherSpringer Verlag
Pages180-194
Number of pages15
ISBN (Print)9783319218427
DOIs
Publication statusPublished - 2015
Event11th International Conference on Data Integration in the Life Sciences, DILS 2015 - Los Angeles, United States
Duration: 9 Jul 201510 Jul 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9162
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Data Integration in the Life Sciences, DILS 2015
Country/TerritoryUnited States
CityLos Angeles
Period9/07/1510/07/15

Bibliographical note

Funding Information:
Funding for Cloud-e-Genome comes from the NIHR (National Institute for Health and Research) and Biomedical Research Centre in the UK.

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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