|Grant Number:||5R01CA106320-08 Interpret this number|
|Primary Investigator:||Zhao, Lue Ping|
|Organization:||Fred Hutchinson Cancer Research Center|
|Project Title:||Methods for Correlating Snp Haplotypes with Cancer|
DESCRIPTION (provided by applicant): The long-term objectives of our research efforts are to develop innovative research design methods and analytic methods for the study of human diseases in the context of maturing genomic technologies (genetic polymorphisms, gene expressions and protein expressions). The primary aims of this proposal are to develop statistical methods and study designs to objectively assess the relationship of genetic polymorphisms in the form of SNPs and haplotypes with disease phenotypes and to investigate the role of gene-environment interactions, believed to play a major role in disease etiology. This objective represents the continuation of our current research project, which focuses on mapping complex diseases. Recent developments in genotyping technologies are revealing interesting local haplotype structures and are continuing to discover many more genetic markers throughout the genome. These provide not only unprecedented opportunities to gain a deeper understanding of disease etiology and to discover biomarkers useful for disease prevention and control, but also present a considerable challenge to the extraction of useful information from the ocean of genomic data now available. While extended pedigrees, nuclear families, sib-pairs have been used in indirect association analyses, direct association analyses may be more efficient and yield sufficient power to detect gene-environment interactions. Therefore, to maximize the power of the association analysis, case-control designs (both matched and unmatched) and cohort study designs will be applied. Methods to be developed will be based on well-established statistical techniques, including: genetic models, estimating equation techniques, likelihood methods, and logistic regression techniques. Where analytical solutions are not possible or computationally prohibitive, bootstrap techniques and Monte Carlo simulation methods will be applied to estimate relevant statistics. A range of statistical methods will be developed, including novel algorithms as necessary, and implemented for dissemination to the research community. Then these methods will be applied data from actual studies for validation and illustration purposes. To ensure the integration of statistics, biology and epidemiology, a team of investigators from multi-disciplinary backgrounds will discuss issues and jointly generate and critique statistical solutions.
Recursive organizer (ROR): an analytic framework for sequence-based association analysis.
Authors: Zhao LP, Huang X
Source: Hum Genet, 2013 Jul;132(7), p. 745-59.
EPub date: 2013 Mar 14.
Sequencing genes in silico using single nucleotide polymorphisms.
Authors: Zhang XC, Zhang B, Li SS, Huang X, Hansen JA, Zhao LP
Source: BMC Genet, 2012 Jan 30;13, p. 6.
EPub date: 2012 Jan 30.
Empirical evaluations of analytical issues arising from predicting HLA alleles using multiple SNPs.
Authors: Zhang XC, Li SS, Wang H, Hansen JA, Zhao LP
Source: BMC Genet, 2011 Apr 25;12, p. 39.
EPub date: 2011 Apr 25.
Predicting multiallelic genes using unphased and flanking single nucleotide polymorphisms.
Authors: Li SS, Wang H, Smith A, Zhang B, Zhang XC, Schoch G, Geraghty D, Hansen JA, Zhao LP
Source: Genet Epidemiol, 2011 Feb;35(2), p. 85-92.
EPub date: 2010 Dec 31.
A systematic search for SNPs/haplotypes associated with disease phenotypes using a haplotype-based stepwise procedure.
Authors: Yang Y, Li SS, Chien JW, Andriesen J, Zhao LP
Source: BMC Genet, 2008 Dec 22;9, p. 90.
EPub date: 2008 Dec 22.
Bias-reduced estimators and confidence intervals for odds ratios in genome-wide association studies.
Authors: Zhong H, Prentice RL
Source: Biostatistics, 2008 Oct;9(4), p. 621-34.
EPub date: 2008 Feb 28.
Observational studies, clinical trials, and the women's health initiative.
Authors: Prentice RL
Source: Lifetime Data Anal, 2007 Dec;13(4), p. 449-62.
EPub date: 2007 Oct 18.
Epidemiologic methods developments: a look forward to the year 2032.
Authors: Prentice RL
Source: Ann Epidemiol, 2007 Nov;17(11), p. 906-10.
EPub date: 2007 Sep 14.
Empirical vs Bayesian approach for estimating haplotypes from genotypes of unrelated individuals.
Authors: Li SS, Cheng JJ, Zhao LP
Source: BMC Genet, 2007 Jan 29;8, p. 2.
EPub date: 2007 Jan 29.
A haplotype-linkage analysis method for estimating recombination rates using dense SNP trio data.
Authors: Zhao LP, Li SS, Shen F
Source: Genet Epidemiol, 2007 Feb;31(2), p. 154-72.
HLA-E, HLA-F, and HLA-G polymorphism: genomic sequence defines haplotype structure and variation spanning the nonclassical class I genes.
Authors: Pyo CW, Williams LM, Moore Y, Hyodo H, Li SS, Zhao LP, Sageshima N, Ishitani A, Geraghty DE
Source: Immunogenetics, 2006 May;58(4), p. 241-51.
EPub date: 2006 Mar 29.
A fine-scale linkage-disequilibrium measure based on length of haplotype sharing.
Authors: Wang Y, Zhao LP, Dudoit S
Source: Am J Hum Genet, 2006 Apr;78(4), p. 615-28.
EPub date: 2006 Feb 13.
Aspects of the design and analysis of high-dimensional SNP studies for disease risk estimation.
Authors: Prentice RL, Qi L
Source: Biostatistics, 2006 Jul;7(3), p. 339-54.
EPub date: 2006 Jan 27.
Toward understanding MHC disease associations: partial resequencing of 46 distinct HLA haplotypes.
Authors: Smith WP, Vu Q, Li SS, Hansen JA, Zhao LP, Geraghty DE
Source: Genomics, 2006 May;87(5), p. 561-71.
EPub date: 2006 Jan 23.
Genetic variation in bactericidal/permeability-increasing protein influences the risk of developing rapid airflow decline after hematopoietic cell transplantation.
Authors: Chien JW, Zhao LP, Hansen JA, Fan WH, Parimon T, Clark JG
Source: Blood, 2006 Mar 1;107(5), p. 2200-7.
EPub date: 2005 Nov 22.
Evaluation of nine strategies for analyzing a cDNA toxicology microarray data set.
Authors: Zhang JJ, Yi T, Zhao LP
Source: J Biopharm Stat, 2005;15(3), p. 403-18.
Toll-like receptor 4 polymorphisms are associated with resistance to Legionnaires' disease.
Authors: Hawn TR, Verbon A, Janer M, Zhao LP, Beutler B, Aderem A
Source: Proc Natl Acad Sci U S A, 2005 Feb 15;102(7), p. 2487-9.
EPub date: 2005 Feb 7.