Name	Yuki Sugaya
	Department	Department of Mathematics, School of Fundamental Science and Technology
	Research Fields	Bioinformatics/Linkage Analysis

I am mainly interested in linkage analysis in genomics, particularly in determining disease locus more accurately dealing properly with pedigree data, based on a concrete mathematical model.
What I have done is to develop an effective procedure to determine a disease locus on a chromosome. It contains two parts. One is a new algorithm called "Probability Inheritance Algorithm" to obtain the maximum likelihood estimate of recombination fractions from pedigree data. Another is to apply a suitable model for linking recombination fraction to a physical distance, reflecting the location of disease locus on a chromosome. The probability inheritance algorithm is a recursive algorithm from generation to generation, so that it is even applicable for the case of large pedigree and many markers. We have developed a Markov model for recombination fraction to reflect interaction between alleles. We have applied our procedure to a real data, Icelandic pedigree data. What we have learned from this application is that informative pedigrees have to be selected, otherwise the estimation of the physical distance of the disease locus from a marker becomes unstable. Also, it is important to make focus on a limited range of loci on a chromosome, because crossover probability is not necessarily homogeneous on a chromosome. Now I compare my procedure to the existing procedure.