title: Entropy-based selection for maternal-fetal genotype incompatibility with application to preterm prelabor rupture of membranes.
abstract: BACKGROUND
  Maternal-fetal genotype incompatibility (MFGI) is increasingly reported to influence human diseases, especially pregnancy-related complications. In practice, it is challenging to identify the ideal incompatibility model for analysis, since the true MFGI mechanism is generally unknown. The underlying MFGI mechanism for different genetic variants can vary, and to use a single incompatibility model for all circumstances would cause power loss in testing MFGI.
  
  
  RESULTS
  In this article, we propose a practical 2-step procedure that incorporates a model selection strategy based on an entropy measurement to select the most appropriate MFGI model represented by data and test the significance of the MFGI effect using the chosen model within the generalized linear regression framework.
  
  
  CONCLUSIONS
  Our simulation studies show that the proposed two-step procedure controls the type I error rate and increase the testing power under various scenarios. In a real data application, our analysis reveals genes having an MFGI effect, which may not be detected with a non-model selection counterpart.
authors.affiliation: Department of Biostatistics, St Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, USA. shaoyu.li@stjude.org.
authors.forename: Shaoyu
authors.initials: S
authors.lastname: Li
authors.forename: Yuehua
authors.initials: Y
authors.lastname: Cui
authors.forename: Roberto
authors.initials: R
authors.lastname: Romero
mesh_terms: D003198:Computer Simulation; D019277:Entropy; D005260:Female; D005322:Premature Rupture of Fetal Membranes / Q000235:genetics*; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D008957:Models, Genetic; D011247:Pregnancy