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Faculty Member

Shelley Bull Ph.D.

Email Address(es)
Office Phone
(416) 586-8245
Office Address
Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital 60 Murray Street, Box #18, 5th floor, room 5-226 Toronto, ON M5T 3L9
Curriculum Vitae
Biostatistics Division
SGS Status
Full Member
Appointment Status
Status Only

Research Interests

  • statistical methods for human genetics
  • categorical data analysis
  • logistic regression modelling
  • analysis of multiple outcomes

Education & Training History

1976 B. Math. University of Waterloo (Statistics)

1977 M. Math. University of Waterloo (Statistics)

1983 Ph.D. The University of Western Ontario (Epidemiology & Biostatistics)

1983-85 Ontario Ministry of Health Postdoctoral Fellow,

Department of Epidemiology and Biostatistics,

The University of Western Ontario

Other Affiliations

Primary Teaching Responsibilities

  • Co-Director of CIHR STAGE (Strategic Training for Advanced Genetic Epidemiology)
  • Co-ordinator of a research seminar and journal club in statistical methods for human genetics research for graduate students and faculty in biostatistics and statistics at the University of Toronto

Professional Summary & Appointments

1985-86 Assistant Professor, Department of Epidemiology and Biostatistics, The Univ of Western Ontario

1986-91 Scientist, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto

1986-93 Assistant Professor, Department of Preventive Medicine and Biostatistics, U of Toronto

1988-92 Associate Member, Graduate Dept of Community Health, School of Graduate Studies

1991- Senior Scientist, Samuel Lunenfeld Research Institute of Mount Sinai Hospital

1992- Member, Graduate Dept of Community Health, U of Toronto

1993-2001 Associate Professor, Public Health Sciences (formerly Preventive Medicine and Biostatistics)

2001-2008 Professor, Dept of Public Health Sciences, U of Toronto

2001- Member, Graduate Department of Statistics, U of Toronto

2008- Professor of Biostatistics, Dalla Lana School of Public Health, U of Toronto

Honours & Awards

  • 2001 Recipient of The Anthony Miller Award For Excellence In Research In Public Health to recognize the outstanding contributions to research of faculty in the Graduate Department of Public Health Sciences
  • Recipient of 2001 Best Paper Award from the International Genetic Epidemiology Society for the article entitled: Design considerations for association studies of candidate genes in families, Genetic Epidemiology 20:149-174, 2001. Authors SB Bull, GA Darlington, CMT Greenwood, J Shin.
  • Senior Investigator, Canadian Institutes of Health Research, 2002-2007
  • 2012 Recipient of IGES Leadership Award, presented by the International Genetic Epidemiology Society in recognition of outstanding leadership through research, teaching, or service to the Society.

Current Research Projects

2009 – 2013 Discovery & characterization of clinically important changes in axillary node-negative breast cancer. IL Andrulis (PI), SB Bull, FP O’Malley, CIHR

2009 – 2015 Regression models for genetic and genomic data. SB Bull (PI). Individual Discovery Grant, Natural Sciences and Engineering Research Council

2010 – 2016 STAGE: An integrated program in statistical and epidemiological training for genetics with a population health impact. F Gagnon (co-PI), SB Bull (co-PI), RJ Hung, G Liu, S Narod, J McLaughlin, E Parra, AD Paterson, S Scherer, L Sun. STIHR Program, CIHR

2012 – 2013 Lipids in type 1 diabetes. AD Paterson (PI), A Boright, A Canty, SB Bull, K Eny. CIHR

2012 – 2015 Genetics of the decline in Glomerular Filtration Rate in Type 1 Diabetes. AD Paterson (PI), SB Bull, A Boright, L Sun, R Klein, B Klein, M Mauer, I de Boer, D Maahs. Juvenile Diabetes Research Foundation (International) .

2012 – 2016 Analysis methods for the next generation of complex trait studies. SB Bull (PI), RV Craiu. Collaborators: Sun L, Paterson AD, Yoo YJ, CIHR

Representative Publications

LY Wu, L Sun, SB Bull. Locus-specific heritability estimation via resampling in linkage scans for quantitative trait loci, Human Heredity, 62:84-96, 2006.L Sun, RV Craiu, AD Paterson, SB Bull. Stratified false discovery control for large-scale hypothesis testing with application to genome-wide association studies, Genetic Epidemiology, 30(6):519-30, Sept 2006.

SB Bull, JP Lewinger, SSF Lee. Confidence intervals for multinomial logistic regression in sparse data, Statistics in Medicine, 2007; 26:903–918

B Xing, CMT Greenwood, SB Bull. A hierarchical clustering method for estimating copy number variation, Biostatistics, 2007 Jul;8(3):632-53.

J Beyene, D Tritchler, SB Bull, KC Cartier, G Jonasdottir, AT Kraja, N Li, NL Nock, E Parkhomenko, JS Rao, CM Stein, R Sutradhar, S Waaijenborg, KS Wang, Y Wang, P Wolkow. Multivariate analysis of complex gene expression and clinical phenotypes with genetic marker data. Genet Epidemiol. 2007;31 Suppl 1:S103-9.

SSF Lee, L Sun, R Kustra, SB Bull. EM-Random Forest and new measures of variable importance for multi-locus quantitative trait linkage analysis, Bioinformatics, 2008 Jul 15;24(14):1603-10.

IW Taylor, R Linding, D Warde-Farley, Y Liu, C Pesquita, D Faria, S Bull, T Pawson, Q Morris, JL Wrana. Dynamic Modularity in Protein Interaction Networks Predicts Breast Cancer Outcome, Nature Biotechnology, 2009 Feb;27(2):199-204.

LY Wu, HA Chipman, SB Bull, L Briollais, K Wang. A Bayesian segmentation approach to ascertain copy number variations at the population level, Bioinformatics 2009 Jul 1;25(13):1669-79.

YJ Yoo, SB Bull, AD Paterson, D Waggott, L Sun; The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group. Were genome-wide linkage studies a waste of time? Exploiting candidate regions within genome-wide association studies. Genet Epidemiol 2010 Feb;34(2):107-118.

C Infante-Rivard, L Mirea, SB Bull. Combining case-control and case-trio data from the same population in genetic association analyses: overview of approaches and illustration with a candidate gene study, American Journal of Epidemiology, 2009 Sep 1;170(5):657-64.

YJ Yoo, D Pinnaduwage, D Waggott, SB Bull, L Sun. Genome-wide association analyses of North American Rheumatoid Arthritis Consortium and Framingham Heart Study data utilizing genome-wide linkage results, BMC Proceedings, 2009 Dec 15;3 Suppl 7:S103.

J Asimit, YJ Yoo, D Waggott, L Sun, SB Bull. Region-based analysis in genome-wide association study of Framingham Heart Study blood lipid phenotypes, BMC Proceedings, 2009 Dec 15;3 Suppl 7:S127.

L Mirea, L Sun, JE Stafford, SB Bull. Using evidence for population stratification bias in combined individual- and family-level genetic association analyses of quantitative traits, Genetic Epidemiology, 2010 July; 34:502-511.

L Sun, A Dimitromanolakis, L Faye, AD Paterson, D Waggott, the DCCT/EDIC Research Group, SB Bull. BR-squared: a Practical Solution to the Winner’s Curse in Genome-Wide Scans, Human Genetics, 2011 May;129(5):545-52.

J Asimit, IL Andrulis, SB Bull. Regression models, scan statistics, and reappearance probabilities to detect regions of association between gene expression and copy number, Statistics in Medicine, 2011 May 10;30(10):1157-78.

L Faye, L Sun, A Dimitromanolakis, SB Bull. A flexible genome-wide bootstrap method that accounts for ranking- and threshold-selection bias in GWAS interpretation and replication study design, Statistics in Medicine, 2011 Jul 10;30(15):1898-912.

Y Yilmaz, SB Bull. Are quantitative trait-dependent sampling designs cost effective for analysis of rare and common variants?” BMC Proceedings 2011; 5(suppl 9):S111.

LL Faye, SB Bull. Two-stage study designs combining GWAS tag SNPs and exome sequencing: accuracy of genetic effect estimates, BMC Proceedings 2011; 5(suppl 9):S64.

JE Bailey-Wilson, JS Brennan, SB Bull, R Culverhouse, Y Kim, Y Jiang, J Jung, Q Li, C Lamina, YLiu, R Mägi, YS Niu, CL Simpson, L Wang, YE Yilmaz, H Zhang, Z Zhang. Regression and Data Mining Methods for Analyses of Multiple Rare Variants in the Genetic Analysis Workshop 17 Mini-Exome Data, Genetic Epidemiology 2011;35 Suppl 1:S92-100.

W Xu, L Mirea, SB Bull, CMT Greenwood. Model-free linkage analysis of a binary trait. Methods in Molecular Biology 2012;850:317-45

L Mirea, L Sun, C Infante-Rivard, SB Bull. Strategies for Genetic Association Analyses Combining Unrelated Case-Control Individuals and Family Trios, American Journal of Epidemiology, 2012 Jul 1;176(1):70-9.

Z Chen, R Craiu, SB Bull. Two-phase stratified sampling designs for regional sequencing. Genetic Epidemiology, 2012 May;36(4):320-32.

AD Paterson, SB Bull. Does familial clustering of risk factors for long-term diabetic complications leave any place for genes that act independently?, Journal of Cardiovascular Translational Research, 2012 Aug;5(4):388-98.

MA Rotondi, SB Bull. Cumulative meta-analysis for genetic association: When is a new study worthwhile? Human Heredity, 2012 Dec;74:61-70.

CL Forse, YE Yilmaz, D Pinnaduwage, FP O’Malley, AM Mulligan, SB Bull, IL Andrulis. Elevated Expression of Podocalyxin is Associated with Lymphatic Invasion, Basal-like Phenotype and Clinical Outcome in Axillary Lymph Node-negative Breast Cancer, Breast Cancer Research and Treatment 2013; 137:709-719.

YE Yilmaz, JF Lawless, IL Andrulis, SB Bull. Insights from mixture cure modeling of molecular markers for prognosis in breast cancer, Journal of Clinical Oncology 2013, Jun 1;31(16):2047-54

SB Bull, Z Chen, K-R Tan, JG Poirier. An exploration of heterogeneity in genetic analysis of complex pedigrees: Linkage and association using WGS data in the MAP4 region, accepted, BMC Proceedings of Genetic Analysis Workshop 18

Z Chen, K-R Tan, SB Bull. Multi-phase analysis by linkage, quantitative transmission disequilibrium, and measured genotype: Systolic blood pressure in complex Mexican-American pedigrees, accepted BMC Proceedings of Genetic Analysis Workshop 18.

S Konigorski, YE Yilmaz, SB Bull. Bivariate genetic association analysis of systolic and diastolic blood pressure by copula models, accepted BMC Proceedings Genetic Analysis Workshop 18.

LL Faye, MJ Machiela, P Kraft, SB Bull, L Sun. Re-ranking sequencing variants in the post-GWAS era for accurate causal variant identification, in press PLoS Genetics.