title: MI-GWAS: a SAS platform for the analysis of inherited and maternal genetic effects in genome-wide association studies using log-linear models.
abstract: BACKGROUND
  Several platforms for the analysis of genome-wide association data are available. However, these platforms focus on the evaluation of the genotype inherited by affected (i.e. case) individuals, whereas for some conditions (e.g. birth defects) the genotype of the mothers of affected individuals may also contribute to risk. For such conditions, it is critical to evaluate associations with both the maternal and the inherited (i.e. case) genotype. When genotype data are available for case-parent triads, a likelihood-based approach using log-linear modeling can be used to assess both the maternal and inherited genotypes. However, available software packages for log-linear analyses are not well suited to the analysis of typical genome-wide association data (e.g. including missing data).
  
  
  RESULTS
  An integrated platform, Maternal and Inherited Analyses for Genome-wide Association Studies (MI-GWAS) for log-linear analyses of maternal and inherited genetic effects in large, genome-wide datasets, is described. MI-GWAS uses SAS and LEM software in combination to appropriately format data, perform the log-linear analyses and summarize the results. This platform was evaluated using existing genome-wide data and was shown to perform accurately and relatively efficiently.
  
  
  CONCLUSIONS
  The MI-GWAS platform provides a valuable tool for the analysis of association of a phenotype or condition with maternal and inherited genotypes using genome-wide data from case-parent triads. The source code for this platform is freely available at http://www.sph.uth.tmc.edu/sbrr/mi-gwas.htm.
authors.affiliation: Human Genetics Center, Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas School of Public Health, Houston, 77030, USA.
authors.forename: A J
authors.initials: AJ
authors.lastname: Agopian
authors.forename: Laura E
authors.initials: LE
authors.lastname: Mitchell
mesh_terms: D004194:Disease / Q000235:genetics*; D005260:Female; D055106:Genome-Wide Association Study; D006801:Humans; D016014:Linear Models; D008297:Male; D008431:Maternal-Fetal Exchange; D011247:Pregnancy; D018570:Risk Assessment / Q000379:methods; D012984:Software