Biography

Dr. Chatterjee received a Ph.D. in statistics in 1999 from the University of Washington, Seattle, where he received the Z.W.Birnbaum and WNAR best student paper awards for his dissertation work on developing efficient methods for analyzing data from two-phase studies. He joined the Division of Cancer Epidemiology and Genetics, NCI, as a Research Fellow in 1999. He was appointed as a principal investigator in 2001, was tenured as a senior investigator in 2004 and became Chief of the Biostatistics Branch in 2008. He is an adjunct Associate Professor at the Department of Biostatistics, John Hopkins University. At NCI, he has received the Fellows Award for Research Excellence (2001), NIH merit award (2003) and the Outstanding Mentoring Award (2006).

Research Interests

Dr Chatterjee has developed an integrated program of methodologic and collaborative research in four major areas of modern molecular epidemiologic studies: (1) genetic association study (2) gene-environment interactions (3) kin-cohort and case-control family study designs and (4) studies of etiologic heterogeneity of diseases using molecular and pathologic markers. His statistical areas of research, which cut across the different scientific disciplines, include regression analysis under complex sampling designs (e.g case-control and two-phase sampling), missing data, multivariate survival analysis and semiparametric inferences. He also actively collaborates in design and analysis of a variety of major cancer epidemiologic studies.

Selected Publications

• Chatterjee N, Chen YH. Maximum-likelihood inference on a mixed conditionally and marginally specified regression model for genetic epidemiologic studies with two-phase sampling. Journal of the Royal Statistical Society, Series B 2007 (In press)
• Chatterjee N, Zeynep K, Moslehi R, Peters U, Wacholder S. Powerful multi-locus tests of genetic association in the presence of gene-gene and gene-environment interactions. American Journal of Human Genetics, 2006 (In press)
• Chatterjee N and Carroll RJ. Semiparametric maximum-likelihood estimation exploiting gene-environment independence in case-control studies. Biometrika 2005; 92:399-418.
• Chatterjee N, Zeynep K and Carroll R. Exploiting gene-environment independence in family-based case-control studies: Increased power for detecting associations, interactions and joint-effects. Genetic Epidemiology 2005; 28:138-156.
• Chatterjee N. A two-stage regression model for epidemiological studies with multivariate disease classification data. Journal of the American Statistical Association, Theory and Methods 2004; 99:127-138.
• Chatterjee N, Chen YH, Breslow NE.  A pseudo-score estimator for regression problems with two-phase sampling. Journal of the American Statistical Association, Theory and Methods 2003; 98:158-168.

Software

• CaseControlIndGX - A MATLAB software package for maximum-likelihood analysis of case-control studies under the assumption of gene-environment independence.
• KinCohort - A MATLAB software package for likelihood-based analysis of kin-cohort data.
• MultAssoc - a MATLAB software package for test of association of a disease with a group of SNPs after accounting for their interaction with another group of SNPs or environmental exposures.
• SAS macro for haplotype analysis of case-control studies

Collaborators

DCEG Collaborators

• Neil Caporaso, Ph.D.; Mitchell Gail, M.D.; Montserrat García-Closas, Ph.D.; Ruth Pfeiffer, Ph.D.; Patricia Hartge, Sc.D.; Richard Hayes, Ph.D., D.D.S.; Sholom Wacholder, Ph.D.

Other NCI Collaborators

• Joanna Shih, Ph.D., Division of Cancer Treatment and Diagnosis, NCI.

Other Scientific Collaborators

• Raymond Carroll, PhD, Texas A&M University
• Jinbo Chen, PhD, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania
• Yi-Hau Chen, PhD, National Taiwan Institute of Statistical Sciences, Academia Sinica, Taipei, Taiwan
• Bhramar Mukherjee, PhD, Department of Biostatistics, U of Michigan, Ann Arbor
• Ulrike Peters, PhD, Fred Hutchinson Cancer Research Center, Seattle.