Spatial rank-based multifactor dimensionality reduction to detect gene-gene interactions for multivariate phenotypes.

Journal: BMC bioinformatics
PMID:

Abstract

BACKGROUND: Identifying interaction effects between genes is one of the main tasks of genome-wide association studies aiming to shed light on the biological mechanisms underlying complex diseases. Multifactor dimensionality reduction (MDR) is a popular approach for detecting gene-gene interactions that has been extended in various forms to handle binary and continuous phenotypes. However, only few multivariate MDR methods are available for multiple related phenotypes. Current approaches use Hotelling's T statistic to evaluate interaction models, but it is well known that Hotelling's T statistic is highly sensitive to heavily skewed distributions and outliers.

Authors

  • Mira Park
    Department of Preventive Medicine, Eulji University, Daejeon, Korea.
  • Hoe-Bin Jeong
    Department of Statistics, Korea University, Seoul,02841, Republic of Korea.
  • Jong-Hyun Lee
    Safety System Research Group, Korea Institute of Industrial Technology (KITECH), Gyeongsan, South Korea.
  • Taesung Park
    Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.