|Grant Number:||5R01CA119225-04 Interpret this number|
|Primary Investigator:||Zhao, Lue Ping|
|Organization:||Fred Hutchinson Cancer Research Center|
|Project Title:||Methods for Assessing Genetic Association with Time-Varying Phenotype|
DESCRIPTION (provided by applicant): This is the revised proposal to the previously submitted RO1 CA119225-01. We appreciate the enthusiasm of the four reviewers and the entire review panel. Equally, we appreciate excellent suggestions to improve our research plan. In addition to clarifying numerous specific points, we have made several major revisions in accordance to reviewers' comments, which include: expansion of Aim 3 (for which the review panel has expressed a particular enthusiasm) at expense of leaving out Aim 4, proposal of a general hazard model to facilitate focused exploration of asymptotic properties for Aim 1 and 2, and reduction of five year proposal to four year proposal. As in the original proposal, our long-term objective is to develop innovative analytic methods for assessing genetic associations with clinical phenotypes, which are typically time-varying and/or censored. While our research does not directly involve humans, methods to be developed enable clinical investigators to design efficient studies, to integrate modern genetics into their research, to extract information efficiently, and to assist them in interpreting findings. Hence, the proposed research enhances our research capability of translating modern genetics into clinical research. Impacted research includes clinical trials, prospective cohort studies, or clinical follow-up studies. In particular, we are going to develop a set of new methods for correlating SNP-haplotypes with time-varying and censored phenotypes, with consideration to haplotypic association, diplotypic associations, gene-environmental interactions, competing risks and recurrences of phenotypes. Further, we will develop methods specifically for addressing phenotypic associations with patient's and donor's SNP-haplotypes, which arise from transplantation research. The preliminary exploration has shown the feasibility of our development. To ensure the practical relevance, we will motivate our development by the long term follow-up cohort of patients who have received bone marrow transplantation at our institution. All methods will be incorporated into the research program (HPIus), publicly available software. While developing methodologies is of priority in this project, we intend to implement all of the new methods into research program, and to release "working" programs to colleagues as soon as methods are accepted through peer review process. After extensive quality control, all working programs will be integrated into a software package, and will be made available to the community.
Predicting Multiallelic Genes Using Unphased And Flanking Single Nucleotide Polymorphisms
Authors: Li S.S. , Wang H. , Smith A. , Zhang B. , Zhang X.C. , Schoch G. , Geraghty D. , Hansen J.A. , Zhao L.P. .
Source: Genetic Epidemiology, 2011 Feb; 35(2), p. 85-92.
Empirical Evaluations Of Analytical Issues Arising From Predicting Hla Alleles Using Multiple Snps
Authors: Zhang X.C. , Li S.S. , Wang H. , Hansen J.A. , Zhao L.P. .
Source: Bmc Genetics, 2011; 12, p. 39.
Sequencing Genes In Silico Using Single Nucleotide Polymorphisms
Authors: Zhang X.C. , Zhang B. , Li S.S. , Huang X. , Hansen J.A. , Zhao L.P. .
Source: Bmc Genetics, 2012; 13, p. 6.
Recursive Organizer (ror): An Analytic Framework For Sequence-based Association Analysis
Authors: Zhao L.P. , Huang X. .
Source: Human Genetics, 2013 Jul; 132(7), p. 745-59.
Tumor Evolution And Intratumor Heterogeneity Of An Oropharyngeal Squamous Cell Carcinoma Revealed By Whole-genome Sequencing
Authors: Zhang X.C. , Xu C. , Mitchell R.M. , Zhang B. , Zhao D. , Li Y. , Huang X. , Fan W. , Wang H. , Lerma L.A. , et al. .
Source: Neoplasia (new York, N.y.), 2013 Dec; 15(12), p. 1371-8.
Deciphering Genome Environment Wide Interactions Using Exposed Subjects Only
Authors: Zhao L.P. , Fan W. , Goodman G. , Radich J. , Martin P. .
Source: Genetic Epidemiology, 2015 Jul; 39(5), p. 334-46.