Hierarchical generalized linear models for multiple groups of rare and common variants: jointly estimating group and individual-variant effects

HIGHLIGHTS

• who: Nengjun Yi et al. from the Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America have published the Article: Hierarchical Generalized Linear Models for Multiple Groups of Rare and Common Variants: Jointly Estimating Group and Individual-Variant Effects, in the Journal: (JOURNAL) of June/23,/2011
• what: The authors propose here a comprehensive hierarchical generalized linear model framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates. The authors develop the mode -finding algorithm by modifying the standard iterative weighted least . . .
  

   

  

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