Research Project
Grant-in-Aid for Young Scientists (B)
World-wide genome-wide association studies (GWASs) using single nucleotide polymorphisms (SNPs) have revealed that SNPs explain small portion of variability of human phenotypes, so-called the missing heritability problem. Current standard method which tests each SNP one at a time may miss contributions by gene-gene or gene-environment interactions. However, statistical methods for those hypotheses are still underdeveloped. In this project, a new statistical testing method is developed. It allows to vary the degrees of freedom for test statistics according to the observed cell frequencies. Simulation studies confirmed that a practically adequate statistical power is achieved.In addition, for genetic prediction problem, new sparse modeling method, smooth-threshold multivariate genetic prediction (STMGP), is developed. It is very rapid even in application to large-scale data such as whole-genome sequencing data, and is shown to have higher prediction accuracy.
All 2016 2015 2014 2013 Other
All Journal Article (10 results) (of which Peer Reviewed: 10 results, Acknowledgement Compliant: 3 results, Open Access: 1 results) Presentation (15 results) (of which Int'l Joint Research: 1 results, Invited: 10 results) Book (1 results) Remarks (1 results)
Genetic Epidemiology
Volume: 40 Issue: 3 Pages: 233-243
10.1002/gepi.21958
Journal of Dermatological Science
Volume: 80 Issue: 2 Pages: 156-158
10.1016/j.jdermsci.2015.07.015
Journal of the Japanese Society of Computational Statistics
Volume: 28 Pages: 53-66
130005434011
Pigment Cell Melanoma Res
Volume: 28 Issue: 2 Pages: 233-5
10.1111/pcmr.12337
Statistics in Medicine
Volume: 33 Issue: 28 Pages: 4934-4948
10.1002/sim.6264
Am J Hum Genet.
Volume: 95 Issue: 3 Pages: 294-300
10.1016/j.ajhg.2014.07.013
PLOS ONE
Volume: 9 Issue: 2 Pages: e55903-e55903
10.1371/journal.pone.0055903
Plant Cell
Volume: 26 (2) Issue: 2 Pages: 636-649
10.1105/tpc.113.121350
Computational Statistics and Data Analysis
Volume: 63 Pages: 31-41
10.1016/j.csda.2013.01.019
Mol Genet Genomic Med
Volume: 1 Issue: 1 Pages: 45-53
10.1002/mgg3.4
http://www.tohoku.ac.jp/japanese/2016/04/press20160415-02.html