Estimation of Killer cell Inhibitory Receptor haplotype frequencies by a constrained maximum likelihood method

The analysis of Killer cell Inhibitory Receptors (KIRs) in terms of haplotypes has only been done through genotyping numerous and selected families. KIR haplotypes have been roughly described as two groups (A and B) based on their gene contents. No further KIR adapted methods have been applied to the estimation of haplotype frequencies using unrelated data. We propose here a maximum likelihood estimation of KIR haplotype frequencies.
Maximum likelihood estimation was developed as an extension of approaches successfully applied to HLA data including the handling of missing values and HLA nomenclature. It has been implemented using an adapted Expectation Maximization (EM) algorithm. KIR types of 11 loci in more than 100 families from a well defined population were used to validate the method in a simulation study. Estimated haplotype frequencies were compared to the known phase based frequencies. Various allele or gene frequency estimation methods were also compared.
We demonstrate the interest and reliability of the haplotype method and underline two major factors affecting the estimations: 1- the sample size effect and 2- the KIR typing resolution. The maximum likelihood haplotype estimation method also provides a more accurate estimation of allele or gene frequencies in a population.
In conclusion we think that such an algorithm opens new perspectives in the analysis of KIR genotypes. A large sample size study is required using known phase data and/or simulations. It would allow a genotype based approach to explore KIR gene haplotype diversity. The haplotype frequencies may then be used in order to compare populations.