Associate Professor, Mathematical Sciences
- PhD, Statistics, Michigan Technological University
- MS, Mathematics, Heilongjiang University (China)
- BS, Mathematics, Heilongjiang University (China)
Qiuying Sha obtained her BS and MS in Mathematics from Heilongjiang University in 1985 and 1988, respectively. In 1988, she accepted a faculty position in the Department of Mathematics at Heilongjiang University and had been working there for 11 years. Sha obtained her PhD in Statistics from Michigan Technological University in 2005. In the same year, she jointed the faculty of the Department of Mathematical Sciences at Michigan Tech. Sha’s research interests include developing statistical methods and computational tools for the analysis and interpretation of genomic data; various methods for genetic linkage and association studies to identify genetic variants underlying complex traits; analysis of genome-wide association data and sequence data under both family-based and population-based designs; microarray data analysis.
Areas of Expertise
- Statistical Genetics
- Applied Statistics
- Sha Q, Wang S, Zhang S (2012) Adaptive clustering and adaptive weighting methods to detect disease associated rare variants. Eur J Hum Genet doi:10.1038
- Sha Q, Wang X, Wang X, Zhang S (2012) Detecting association of both rare and common variants by testing an optimally weighted combination of variants. Genetic Epidemiol 36:561-571
- Fang S, Sha Q, Zhang S (2012) Two adaptive weighting methods to test for rare variant associations in family-based designs. Genetic Epidemiol 36:499–507
- Sha Q, Zhang Z, Zhang S (2011) Joint analysis for genome-wide association studies in family-based designs. PLoS ONE 6(7): e21957.
- Sha Q, Zhang Z, Zhang S (2011) An improved score test for multi-marker association. Genetic Epidemiol, 35: 350-359.
- Niu A, Zhang S, Sha Q* (2011) A novel method to detect gene-gene interactions in structured populations: MDR-SP. Ann Hum Genet 75:742-754
- Zhang Z, Sha Q, Wang X, Zhang S (2011) Two strategies of extreme values and iterative regression and their hybrid approach for rare variants in association studies. BMC Proceedings 5(Suppl 9):S112
- Sha Q, Zhang S (2011) A test of Hardy Weinberg equilibrium in structured populations. Genetic Epidemiol 35:671-678
- Qin H, Feng T, Zhang S, Sha Q (2010) A data-driven weighting scheme for family-based genome-wide association studies. Eur J Hum Genet, 18:596-603.
- Zhang Z, Niu A, Sha Q (2010) Identify interaction genes in genome-wide association studies using a model-based two-stage approach. Ann Hum Genet, 74(5):406-415.