Statistical Genetics

Yamada Ryo, M.D., Ph.D. Professor  btn

Diversity is a fundamental feature of biology and medicine. Recent developments in genomics and related research fields with massive data have provided great opportunities to investigate biological and medical diversity. Statistical genetics is the study to understand biological and medical diversity by combining genetic and environmental components with mathematical methods. It is becoming more and more interdisciplinary and it is a combination of mathematics, statistics, information science, computer science, genetics, molecular biology and medicine. Any one of these backgrounds is helpful and you can start statistical genetics from any one of them.

Research and Education

We study various biological and pathological phenomena by analyzing data of multiple omics technologies, such as genome, epigenome, transcriptome, proteome, and metabolome. Our studies are divided into two types. One is the development of statistical methods to analyze omics data. The other is to collaborate with other researchers, assisting them to design studies and analyzing their data. Because development of new analytic methods depends on deep understanding of phenomena themselves, we consider the two types of our studies are in the complementary relation. This is the reason why we are in the collaboration with multiple research groups varying in their size and fields. We are particularly working on two particular projects from 2016. One is on “discrete data structure-based statistics” which is a new field applying specific data structures suitable for computation to data mining procedures. The other is on “statistical characterization of shapes and movements of in vivo cells”.
In addition, we participate in the joint degree program with McGill University, Canada, to facilitate interdisciplinary education on quantitative biology.

r-028-1①Books in the related fields.
r-028-2②Data, Grabbing data and understanding of data.

Recent Publications

1. Murakami,R.; Matsumura,N.; Brown,J.B.; Higasa,K.; Tsutsumi,T.; Kamada,M.; Abou-Taleb,H.; Hosoe,Y.; Kitamura,S.; Yamaguchi,K.; Abiko,K.; Hamanishi,J.; Baba,T.; Koshiyama,M.; Okuno,Y.; Yamada,R.; Matsuda,F.; Konishi,I.; Mandai,M. (2017) Exome Sequencing Landscape Analysis in Ovarian Clear Cell Carcinoma Shed Light on Key Chromosomal Regions and Mutation Gene Networks Am.J.Pathol., 2017, 187, 10, 2246-2258
2. Morimoto,C.; Manabe,S.; Kawaguchi,T.; Kawai,C.; Fujimoto,S.; Hamano,Y.; Yamada,R.; Matsuda,F.; Tamaki,K. (2016) Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms PLoS One 2016, 11, 7, e0160287
3. Fujii,Y.; Narita,T; Tice,R.R.; Takeda,S; Yamada,R. (2016) Isotonic Regression Based-Method in Quantitative High-Throughput Screenings for Genotoxicity. Dose-response 13(1) 13-045.Fujii
4. Narahara,M.; Higasa,K.; Nakamura,S.; Tabara,Y.; Kawaguchi,T.; Ishii,M.; Matsubara,K.; Matsuda,F.; Yamada,R. (2014) Large-scale East-Asian eQTL mapping reveals novel candidate genes for LD mapping and the genomic landscape of transcriptional effects of sequence variants. PLoS One, 9, 6, e100924
5.Okada,Y.; Wu,D.; Yamada,R.; Plenge,R.M. et. Al . (2014) Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 7488,376-381

Statistical Genetics

Professor: Yamada Ryo