Fei Zou

The Zou group is interested in the statistical properties of theoretical methods used to interpret genetic data, such as quantitative traits, association studies, gene expression profiling, etc. Most of their work has focused on developing robust and efficient methodologies for linkage mapping of complex traits, where the data are often complicated by statistical problems such as outliers, gross errors or heavy-tailed distributions. Multiple comparisons resulting from whole-genome scans in linkage studies can also complicate the threshold and power calculations. In particular, they have developed a synthesized multipoint method to analyze the linkage disequilibrium between multiple SNP markers (single-nucleotide polymorphisms) and the disease gene of interest. This method was tested on datasets for two different genetic diseases where the causative gene is known--cystic fibrosis and hereditary hemochromatosis. In both cases, the disease locus was correctly identified. Haplotype data are also extremely valuable in studies of linkage disequilibrium, where large chromosomal segments are used for mapping rather than single base-pair markers. The Zou group is currently developing a unified strategy that integrates haplotype estimation into the multipoint method to create a more powerful tool for mapping complex traits.

Another ongoing research interest is in the area of statistical genomics. They are interested in developing statistical tools for comparative genomics of model and non-model plant species, such as Arabidopsis thaliana and Brassica oleracea. DNA microarrays are an important tool for comparative genomics since they make it possible to monitor the expression level of thousands of genes simultaneously. There are many statistical issues and parameters that are important in analyzing microarray data, such as sample size, power calculations, etc. These and other statistical problems associated with whole-genome datasets and comparisons are being actively pursued.

Selected Publications:
Zou F, Xu Z, Vision T. (2006) Assessing the significance of quantitative trait loci in replicable mapping populations. Genetics. 174(2):1063-8.

Drumm ML, Konstan MW, Schluchter MD, Handler A, Pace R, Zou F, Zariwala M, Fargo D, Xu A, Dunn JM, Darrah RJ, Dorfman R, Sandford AJ, Corey M, Zielenski J, Durie P, Goddard K, Yankaskas JR, Wright FA, Knowles MR; Gene Modifier Study Group. (2005) Genetic modifiers of lung disease in cystic fibrosis. N Engl J Med 353:1443-53.

Hu J, Zou F, Wright FA. (2005) Practical FDR-based sample size calculations in microarray experiments. Bioinformatics 21:3264-72.

Xu Z, Zou F, Vision TJ. (2005) Improving quantitative trait loci mapping resolution in experimental crosses by the use of genotypically selected samples. Genetics 170:401-8.

Zou F, Fine JP, Hu J, and Lin DY. (2004) An efficient resampling method for assessing genome-wide statistical significance in mapping quantitative trait loci. Genetics 168:2307-2316.







					The Zou group is interested in the statistical properties of theoretical methods used to interpret genetic data, such as quantitative traits, association studies, gene expression profiling, etc. Most of their work has focused on developing robust and efficient methodologies for linkage mapping of complex traits, where the data are often complicated by statistical problems such as outliers, gross errors or heavy-tailed distributions. Multiple comparisons resulting from whole-genome scans in linkage studies can also complicate the threshold and power calculations. In particular, they have developed a synthesized multipoint method to analyze the linkage disequilibrium between multiple SNP markers (single-nucleotide polymorphisms) and the disease gene of interest. This method was tested on datasets for two different genetic diseases where the causative gene is known--cystic fibrosis and hereditary hemochromatosis. In both cases, the disease locus was correctly identified. Haplotype data are also extremely valuable in studies of linkage disequilibrium, where large chromosomal segments are used for mapping rather than single base-pair markers. The Zou group is currently developing a unified strategy that integrates haplotype estimation into the multipoint method to create a more powerful tool for mapping complex traits. Another ongoing research interest is in the area of statistical genomics. They are interested in developing statistical tools for comparative genomics of model and non-model plant species, such as Arabidopsis thaliana and Brassica oleracea. DNA microarrays are an important tool for comparative genomics since they make it possible to monitor the expression level of thousands of genes simultaneously. There are many statistical issues and parameters that are important in analyzing microarray data, such as sample size, power calculations, etc. These and other statistical problems associated with whole-genome datasets and comparisons are being actively pursued. Selected Publications: Zou F, Xu Z, Vision T. (2006) Assessing the significance of quantitative trait loci in replicable mapping populations. Genetics. 174(2):1063-8. Drumm ML, Konstan MW, Schluchter MD, Handler A, Pace R, Zou F, Zariwala M, Fargo D, Xu A, Dunn JM, Darrah RJ, Dorfman R, Sandford AJ, Corey M, Zielenski J, Durie P, Goddard K, Yankaskas JR, Wright FA, Knowles MR; Gene Modifier Study Group. (2005) Genetic modifiers of lung disease in cystic fibrosis. N Engl J Med 353:1443-53. Hu J, Zou F, Wright FA. (2005) Practical FDR-based sample size calculations in microarray experiments. Bioinformatics 21:3264-72. Xu Z, Zou F, Vision TJ. (2005) Improving quantitative trait loci mapping resolution in experimental crosses by the use of genotypically selected samples. Genetics 170:401-8. Zou F, Fine JP, Hu J, and Lin DY. (2004) An efficient resampling method for assessing genome-wide statistical significance in mapping quantitative trait loci. Genetics 168:2307-2316.

		contact information: [phone] (919) 843-4822 [email] [website]