Genomic imprinting is a mechanism by which only one copy of a gene pair is 
expressed, and this expression is determined by the parental origin of the copy. 
The deregulation of imprinted genes has been implicated in a number of human 
diseases. The Imprinted Gene Catalogue now has more than 200 genes listed, and 
estimates based on mouse models suggest many more may exist in humans. 
Therefore, the development of methods to identify such genes is important. In 
this communication, we present a parametric model-based approach to analyzing 
arbitrary-sized pedigree data for genomic imprinting. We have modified widely 
used LINKAGE program to incorporate our proposed approach. In addition, our 
approach allows for the use of sex-specific recombinations in the analysis, 
which is of particular importance in a genome-wide analysis for imprinted genes. 
We compared our imprinting analysis approach to that implemented in the 
GENEHUNTER-IMPRINT program using simulation studies as well as by analyzing 
causal genes in Angelman's syndrome families, which are known to be imprinted. 
These analyses showed that the proposed approach is very powerful for detecting 
imprinted genes in large pedigrees.