Michigan Technological University

Department of Mathematical Sciences

Qiuying Sha

Qiuying Sha

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Associate Professor

  • PhD, Statistics, Michigan Technological University
  • MS, Mathematics, Heilongjiang University (China)
  • BS, Mathematics, Heilongjiang University (China)

Biography

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.

Links of Interest

Areas of Expertise

  • Statistical Genetics
  • Applied Statistics

Recent Publications

  • 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.
  • 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.
  • 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.
  • Sha Q, Zhang Z, Schymick JC, Traynor BJ, Zhang S (2009) Genome-wide association reveals three SNPs associated with sporadic amyotrophic lateral sclerosis through their interactions. BMC Med Genet, 10:86.
  • Tang R, Tao F, Sha Q, Zhang S (2009) A new sliding-window test via principal component analysis. Ann Hum Genet, 73: 631–637.
  • Sha Q, Tang R, Zhang S (2009) Detect susceptibility genes for Rheumatoid Arthritis based on a novel sliding-window method. BMC Proc, 3:S14.
  • Niu A, Zhang Z, Sha Q (2009) Application of seventeen two-locus models in genome-wide association studies by two-stage strategy. BMC Proc, 3:S26.
  • Wang X, Qin H, Sha Q (2009) Incorporating multiple-marker information to detect risk loci for rheumatoid arthritis. BMC Proc, 3:S28.
  • Cui X, Sha Q, Zhang S, Chen H-S (2009) A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis data. BMC Proc, 3:S43.
Michigan Technological University is an equal opportunity educational institution/equal opportunity employer.

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