GPU Accelerated Browser for Neuroimaging Genomics

Alzheimer’s Disease Neuroimaging Initiative

Research output: Contribution to journalArticle

Abstract

Neuroimaging genomics is an emerging field that provides exciting opportunities to understand the genetic basis of brain structure and function. The unprecedented scale and complexity of the imaging and genomics data, however, have presented critical computational bottlenecks. In this work we present our initial efforts towards building an interactive visual exploratory system for mining big data in neuroimaging genomics. A GPU accelerated browsing tool for neuroimaging genomics is created that implements the ANOVA algorithm for single nucleotide polymorphism (SNP) based analysis and the VEGAS algorithm for gene-based analysis, and executes them at interactive rates. The ANOVA algorithm is 110 times faster than the 4-core OpenMP version, while the VEGAS algorithm is 375 times faster than its 4-core OpenMP counter part. This approach lays a solid foundation for researchers to address the challenges of mining large-scale imaging genomics datasets via interactive visual exploration.

Original languageEnglish (US)
Pages (from-to)393-402
Number of pages10
JournalNeuroinformatics
Volume16
Issue number3-4
DOIs
StatePublished - Oct 1 2018

Keywords

  • Alzheimer’s disease
  • Data mining
  • GPU
  • Genomics
  • MRI
  • Versatile gene based association study

ASJC Scopus subject areas

  • Software
  • Neuroscience(all)
  • Information Systems

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  • Cite this

    Alzheimer’s Disease Neuroimaging Initiative (2018). GPU Accelerated Browser for Neuroimaging Genomics. Neuroinformatics, 16(3-4), 393-402. https://doi.org/10.1007/s12021-018-9376-y