Grant Number:	1R13CA168331-01A1 Interpret this number
Primary Investigator:	Satagopan, Jaya
Organization:	Sloan-Kettering Inst Can Research
Project Title:	Advances in Statistical Methods for Cancer Genetic Epidemiology
Fiscal Year:	2013

DESCRIPTION (provided by applicant): The recent advances in genomics technology, coupled with increasing investigation of putative environmental carcinogens, have led to revolutionary progress in evaluating and identifying genetic and environmental factors for various cancers and cancer-related traits through focused studies of candidate pathways as well as high throughput genome-wide association studies. Statistical methods play a pivotal role in the efficient design of these studies and in the successful analysis of the resulting data. Several novel statistical methods have been developed for addressing the critical needs of cancer research studies based on the rapidly growing genomics technology. These include innovative study designs, novel analytic methods for studying interactions between risk factors, integration of multiple data types and incorporation of pathway information for improving the detection of cancer risk factors, evaluation of rare genetic variants, and improved methods for estimating the absolute risk of cancer. The availability of genome-wide somatic mutation data and the ability to sequence the genome to obtain information on rare genetic variants have stimulated the investigation of novel hypotheses such as clonality of cancer and etiologic heterogeneity of cancer subtypes. Therefore, a two-day symposium on "Advances in Statistical Methods for Cancer Genetic Epidemiology" would be important and timely. The Specific Aims of this symposium are: (1) to promote discussions and collaborations among leading and emerging experts in the area of statistical and computational methods with application to cancer research with emphasis on molecular epidemiology for accelerating the development and use of novel statistical and computational methods; (2) to promote a forum for the interchange of ideas and expertise for evaluating data arising from a variety of study designs; (3) to encourage the development of user-friendly software packages; (4) to promote the use of publicly available data to assess these statistical and computational methods; and (5) to publish select papers from this workshop in the journal Genetic Epidemiology. This is an open symposium with an emphasis on diversity, where extensive efforts will be made to include women, under-represented minority, and junior researchers in the program.





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