Dr. Celia M. T. Greenwood
Senior Investigator, Centre for Clinical Epidemiology, Lady Davis Institute
Associate Professor, Department of Oncology, Department of Epidemiology, Biostatistics and Occupational Health, and Division of Cancer Epidemiology, McGill University
Dr. Greenwood joined the LDI from the Hospital for Sick Children and the Dalla Lana School of Public Health in Toronto. She is a statistician with an interest in methodology for the analysis of genetic and genomic data. Her methodological work spans family studies looking for patterns of inheritance of disease-causing genes, case-control studies looking for associations between anonymous markers and disease status, gene expression studies examining differences between patient groups or tissues, and estimation of copy number variation in the genome. Some of the theoretical work developed by her students includes: a haplotype estimation algorithm using hidden Markov models, a flexible method for estimating disease-gene relationships in sparse data using Dirichlet process mixtures, and tree-based models for estimating the evidence for linkage in the presence of heterogeneity.
She led the statistical analysis team in a genome-wide association study of colorectal cancer, where a new locus was identified conferring increased risk. In the context of that study, the team proposed, and used, a novel stratified method for assessing false discovery rates, and developed a computationally-efficient method for empirically estimating large numbers of p-values for haplotype-disease associations.
Major Research Activities
For many years, Dr. Greenwood has been working on issues of data quality and measurement in genomic data, and how measures of quality can be developed and used to improve the detection of important signals in high-throughput genomic data. In particular, one focus of this research has been in data integration, where information from different experiments is combined to improve prediction performance or signal detection.
Pingzhao Hu, Celia MT Greenwood, Joseph Beyene. Using the ratio of means as the effect size measure in combining results of microarray experiments. BMC Systems Biology 2009, 3:106. doi:10.1186/1752-0509-3-106.
Babak Shahbaba, Andrew J Gentles. Joseph Beyene, Sylvia K. Plevritis, Celia M.T. Greenwood (2009). A Bayesian nonparametric method for model evaluation. Journal of Nonparametric Statistics, 21(2): 379-396.
Celia MT Greenwood, Shuying Sun, Justin Veenstra, Nancy Hamel, Bethany Niell, Stephen Gruber, William D Foulkes (2010). How old is this mutation? A study of three Ashkenazi Jewish founder mutations. BMC Genetics 11:39.