- Statistical genetics to analyze large-scale genome data
- Supercomputers for genome analysis
- Using genome data to study disease develoment and drug discovery
- Development of new statistical genetics methods
- Educating future statistical genetics
Gene statistics and genome data for the study of disease development and drug discovery
Statistical genetics is the field that uses statistical methods to connect genome data with phenotypes. The field has grown considerably in recent years due to the excessive genomic data gained from next generation sequencers.
The lab uses statistical genetics to study disease pathology, drug discovery, and personalized medicine. International collaborations on large-scale genome analysis have revealed key genes thought to play a role in disease development [1,2,3]. New drug discovery  and drug repositioning [5} has come from a combination of statistical genetics with genome analysis and the use of drug databases and HLA biomarkers [6,7].
Statistical genetics brings together a number of scientific fields, including statistics, genetics, clinical medicine and information science, which is why there still remains a small number of experts in Japan. The lab therefore commits a part of its efforts to education, by organizing seminars and classes that teach this underdeveloped field.
1. Y Okada, X Sim, MJ Go, et al. Nature Genetics 44 (8), 904-909, 2012.
2. Y Okada, C Terao, K Ikari, et al. Nature Genetics 44 (5), 511-516, 2012.
3. Y Okada, M Kubo, H Ohmiya, et al. Nature genetics 44 (3), 302-306, 2012.
4. Y Okada, D Wu, G Trynka, et al. Nature 506 (7488), 376-381, 2014.
5. Y Okada, T Muramatsu, N Suita, et al. Scientific Reports 6, 22223, 2016.
6. Y Okada, Y Momozawa, K Ashikawa, et al. Nature genetics 47 (7), 798-802, 2015.
7. Y Okada, A Suzuki, K Ikari, et al. American Journal of Human Genetics 99 (2), 366-374, 2016.