Dajiang (Jeff) Liu
My research interests and experiences are broad, but most of my research is focused on developing statistical methods for mapping complex traits due to rare variants using second generation sequencing data. My research lead to the development of the kernel based adaptive cluster (KBAC) method for detecting associations with rare variants in case control studies. I have developed a mixed effects likelihood framework MEGA-rvQTL for quantitative trait loci mapping using unrelated individuals and pedigree samples with extreme phenotypes. I also proposed a flexible likelihood approach PLEIO-MAP for dissecting gene pleiotropy and modeling multiple phenotypes using non randomly ascertained samples. In addition, I investigated novel replication study designs combining sequencing with traditional high throughput genotyping platforms.
- Ph.D. in Statistics (expected May 2011) Rice University
Thesis title: Using Second Generation Sequencing Data
- Advisor: Prof. Suzanne M. Leal
Co-advisor: Prof. Marek Kimmel
- M.A. in Mathematics, 2006, Rice University
- B.S. in Applied Mathematics and Economics (double major), 2003, Peking University
Liu DJ, Leal SM. (2010) Replication strategies for rare variant complex trait association studies using next generation sequencing. Am J Hum Genet. 87(6):790-801.
Liu, DJ, Leal SM (2010) A novel adaptive method for the analysis of next generation sequencing data to detect complex trait associations with rare variants due to gene main effects and interactions. PLoS Genet. 6(10): e1001156.
Kondkar, AA, Bray, MS, Leal, SM, Nagalla, A, Liu, DJ, Jin Y, Dong, JF, Ren Q, Whiteheart, SW, Shaw, C, Bray, PF. (2010) VAMP8/ENDOBREVIN is overexpressed in hyperreactive human platelets: suggested role for platelet microRNA. J Thromb Haemost. Feb;8(2):369-78.