TY - JOUR AU - Motsinger-Reif, Alison A. PY - 2008 DA - 2008/12/30 TI - The effect of alternative permutation testing strategies on the performance of multifactor dimensionality reduction JO - BMC Research Notes SP - 139 VL - 1 IS - 1 AB - Multifactor Dimensionality Reduction (MDR) is a novel method developed to detect gene-gene interactions in case-control association analysis by exhaustively searching multi-locus combinations. While the end-goal of analysis is hypothesis generation, significance testing is employed to indicate statistical interest in a resulting model. Because the underlying distribution for the null hypothesis of no association is unknown, non-parametric permutation testing is used. Lately, there has been more emphasis on selecting all statistically significant models at the end of MDR analysis in order to avoid missing a true signal. This approach opens up questions about the permutation testing procedure. Traditionally omnibus permutation testing is used, where one permutation distribution is generated for all models. An alternative is n-locus permutation testing, where a separate distribution is created for each n-level of interaction tested. SN - 1756-0500 UR - https://doi.org/10.1186/1756-0500-1-139 DO - 10.1186/1756-0500-1-139 ID - Motsinger-Reif2008 ER -