A Marginal Likelihood Model for Family‐Based Data

Abstract

SummaryThis paper presents a marginal likelihood model for family-based data based upon the transmission of marker alleles from each heterozygous parent to his/her affected children. The proposed model, extending the maximumlikelihood-binomial (MLB) method and the disequilibrium maximum-likelihood-binomial (DMLB) method Abel & Müller-Myhsok, 1998;Huang & Jiang, 1999), is adaptive to linkage disequilibrium (LD) and linkage heterogeneity. Compared with other procedures, the likelihood ratio test (LRT) derived from the proposed model enjoys superior qualities. First, simulations indicate that the power of the LRT is greater than that of the TDT or DMLB in all of our studied scenarios. Second, when we applied the LRT and other tests to a Tourette Syndrome data, the result was data favorable to the use of the LRT. Therefore, we recommend the use of the LRT as an additional linkage test wherever applicable, especially when the amount of LD is uncertain.

The Transmission Disequilibrium/Heterogeneity Test with Parental-Genotype Reconstruction for Refined Genetic Mapping of Complex Diseases

“…The TDH test was shown to be an efficient score test of the general mixture likelihood derived in Shao 4 which is a summation of two parts, a transmission/disequilibrium test TDT part which utilizes the LD information and a transmission heterogeneity test THT part that utilizes IBD-sharing information. To see that the THT utilizes IBD-sharing information, it should be pointed out that general mixture likelihood contains the mixture binomial likelihood discussed in Huang and Jiang 13 and Lo et al 5 , and the test statistic of the classical mean test for affected sib-pairs ASPs is a special case of the THT statistic with n ai 2 in Shao 4 . The classical mean test for affected sib-pairs is the most well-known IBD sharing-based linkage test 14 .…”

“…intensive 5,17 . Many existing linkage tests and algorithms such as the likelihood ratio test discussed in Lo et al 5 would be too computationally intensive for genomewide studies or when the number of genotyped markers is large.…”