Fast and Accurate Detection of Complex Imaging Genetics Associations Based on Greedy Projected Distance Correlation

Jian Fang, Chao Xu, Pascal Zille, Dongdong Lin, Hong Wen Deng, Vince D. Calhoun, Yu Ping Wang

Research output: Contribution to journalArticle

Abstract

Recent advances in imaging genetics produce large amounts of data including functional MRI images, single nucleotide polymorphisms (SNPs), and cognitive assessments. Understanding the complex interactions among these heterogeneous and complementary data has the potential to help with diagnosis and prevention of mental disorders. However, limited efforts have been made due to the high dimensionality, group structure, and mixed type of these data. In this paper, we present a novel method to detect conditional associations between imaging genetics data. We use projected distance correlation to build a conditional dependency graph among high-dimensional mixed data, and then use multiple testing to detect significant group level associations (e.g., regions of interest-gene). In addition, we introduce a scalable algorithm based on orthogonal greedy algorithm, yielding the greedy projected distance correlation (G-PDC). This can reduce the computational cost, which is critical for analyzing large volume of imaging genomics data. The results from our simulations demonstrate a higher degree of accuracy with G-PDC than distance correlation, Pearson's correlation, and partial correlation, especially when the correlation is nonlinear. Finally, we apply our method to the Philadelphia Neurodevelopmental data cohort with 866 samples including fMRI images and SNP profiles. The results uncover several statistically significant and biologically interesting interactions, which are further validated with many existing studies. The MATLAB code is available at https://sites.google.com/site/jianfang86/gPDC.

Original languageEnglish (US)
Pages (from-to)860-870
Number of pages11
JournalIEEE transactions on medical imaging
Volume37
Issue number4
DOIs
StatePublished - Apr 2018
Externally publishedYes

Keywords

  • Imaging genetics
  • SNP
  • distance correlation
  • fMRI
  • orthogonal greedy algorithm
  • projected distance correlation

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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