The Data Science Platform facilitates the development, management, analysis, and linkage of clinical, administrative, genomic and other data resources for patient-oriented research. The Platform works closely with the Manitoba Centre for Health Policy (MCHP), Regional Health Authorities, Manitoba Health, Seniors and Active Living, Public Health Agency of Canada, Canada Institute for Health Information, other provincial/ territorial SPOR SUPPORT Units, and other stakeholders.
Scientists lead and participate in a variety of projects to improve patient outcomes. Methodological innovations have focused on:
- Modelling of genomics and microbiome data
- Database quality assessment
- Population health surveillance methods
- Disease risk prediction models
- Measuring and modeling latent variables, such as health-related quality of life
Our team offers a range of short courses, workshops, and seminars including:
- Biostatistics group consulting sessions
- Workshops on advanced statistical methods, such as propensity score models and missing data models
- Resident training sessions on introductory biostatistics
- Bioinformatics workshops
- Introductory and intermediate clinical data management workshops
- Internships for undergraduate and graduate students
The Biostatistics Group serves as a resource of statistical expertise for researchers and students across the University of Manitoba, as well as at other universities. Expertise is provided in design, measurement, and analysis of health and health-related data.
The Biostatistics Group operates on a cost recovery model, however, there are accommodations for students and faculty members who do not have funds to support their research.
Examples of academic collaborations include:
• Consults on research design, data collection, data analysis, and results interpretation.
• Develops and adapts new research methods for research projects.
• Participates in grant planning, and proposal development.
• Provides advice on statistical computing for a variety of software, including SAS, SPSS, R and M-plus.
• Sample size and power calculations.
Support for New Clinician Scientists
The Biostatistics Group offers multiple training opportunities for the next generation of clinician scientists. The Royal College of Physicians and Surgeons has added a new scholarly competency to their training standards for resident and fellows (CanMEDS 2015), which will oblige trainees to formally study research methods and conduct a scholarly or research project during their training. To support resident and fellow research, the Biostatistics Group offers the following complementary programs and services:
- Open House sessions, where residents and fellows can meet one or more biostatistical consultants to discuss their study design and analysis questions. These sessions are co-sponsored by the College of Medicine’s Office of Postgraduate Medical Education (PGME). Registration is required, but there are no costs to participate. Please contact the PGME office for more information (firstname.lastname@example.org).
- A series of 3 academic half day workshops on statistical methods that cover the following topics: (i) study design and sample size calculations, (ii) introduction to data analysis, and (iii) statistical computing (laboratory session). For more information, please complete the intake form CHI Intake Form.
- One-on-one consulting sessions. Up to five hours of no-cost consulting time is available for inquiries about study design and analysis. For more information, please complete the intake form CHI Intake Form.
- Multi-day workshops on advanced topics, including propensity scores models for observational data, hierarchical models for longitudinal/ multi-level studies, and latent class analysis. For more information on upcoming workshops, visit the following (http://chimb.ca/events).
We strongly encourage residents and fellows to undertake their own statistical analysis. However, for specialized analyses, residents and fellows may engage a biostatistical consultant on a fee-for-service basis. Some clinical departments may have specific funds set aside for training purposes to support the costs of a consultant. Please contact your department for further information about funding availability.
In addition, the Biostatistics Group offers workshops on the use of statistical software such as R, SAS, and SPSS. For more information, please visit http://chimb.ca/events
For inquiries, please complete CHI Intake Form.
The Bioinformatics and Computational Biology Group is a multidisciplinary team of computer science, statistics and biology faculty, staff, and students. We offer expertise in the analyses of big omics datasets for collaborative research projects and fee-for-service projects, including:
- Study design and analytical planning
- Sample size and power calculations
- Interpreting and summarizing results
- Assistance for developing grant proposals
We are specialized in (1) array-based gene expression, methylation and proteomic analysis; (2) DNA-Seq, RNA-Seq, Chip-Seq and methylation sequencing analysis; (3) statistical genetic analysis; (4) copy number variation analysis; (5) microbiome and metagenomic analysis; (6) pathway and/or gene set based analysis and enrichment map visualization.
For inquiries, please complete CHI Intake Form.
The Clinical Research Data Group serves as a resource for clinical researchers to develop new databases, and explore existing health databases in Manitoba. We aim to provide researchers with a central location for secure storage of clinical databases.
- Metadata Repository: a collection of metadata (data about data) that captures information about health status, factors that influence health status, health care, public health, and health–related interventions from the clinical trials, observational studies, and cohort studies in Manitoba. The Metadata Repository will help to promote the use of existing datasets for secondary analysis, thereby fostering research collaboration and innovation within Manitoba.
The Secure Research Environment (SRE) is a virtualized system maintained by MedIT of the Max Rady College of Medicine. It houses the local production instance of REDCap, a clinical research data management program supported by CHI, as well as a growing collection of analytic tools.
- Analysis of administrative health data, clinical registries, and electronic medical record data
For inquiry, please complete CHI Intake Form.
We offer fee-for-service consulting for researchers, clinicians, students and program staff. Some consulting is available free of charge, including study design an analysis planning for grant submissions. Graduate students, residents, and fellows have access to a limited amount of no-cost consulting services.
Dr. Lisa Lix joined the University of Manitoba in September 2012 as a Manitoba Research Chair and to lead the development of the Data Science platform within the George and Fay Yee Centre for Healthcare Innovation at the University of Manitoba. Prior to this, she was Centennial Chair in the School of Public Health at the University of Saskatchewan (2008 – 2012), and continues to direct a Population Health Data Laboratory at that University, funded by the Canadian Foundation for Innovation, which focuses on methodological techniques for the analysis of administrative health data.
Dr. Lix’s areas of research expertise include health services research methods, statistical methods for evaluation of the quality of administrative health databases, the analysis of repeated measures and longitudinal data, and robust statistical methods for patient-reported outcomes. She collaborates widely on projects about population health and the association between chronic disease and quality of life. Dr. Lix has extensive experience working with administrative health databases from multiple provinces and this has provided her with unique insights into new methodological research opportunities.
She is currently leading a three-year Canadian Institutes of Health Research (CIHR)-funded project that will conduct comparative investigations of the quality of physician billing claims databases from Newfoundland and Labrador, Nova Scotia, Manitoba, and Saskatchewan.
Director, Data Science
Dr. Robert Balshaw joined the Data Science Platform of the George and Fay Yee Centre for Healthcare Innovation as a Senior Biostatistician in the fall of 2017. Before this, Rob was a Senior Scientist for 5 years at the BC Centre for Disease Control, and for 14 years was head of biostatistics at Syreon Corporation (Vancouver), a contract research organization conducting clinical trials for the pharmaceutical industry. He obtained his bachelor’s and master’s degrees from the Department of Statistics at the University of Manitoba, and his PhD in Statistics from Simon Fraser University.
Dr. Balshaw’s expertise includes the planning, design, implementation and analysis of clinical trials, the discovery and validation of ‘omic biomarkers, secondary use of linked administrative databases, the use of observational data to approximate results of randomized studies, and the analysis of longitudinal and life-history data. He has collaborated with a wide variety of researchers, from graduate students through big pharma, and has led or been part of literally hundreds of statistical projects, big and small.
Dennis Bayomi is the Research Data Administrator, serving as CHI's REDCap training and support lead. He organizes and conducts training sessions for research teams interested in using REDCap and provides support for projects using that system.
Since 2001, Dennis has also been working part-time as a database/research analyst for the Manitoba Follow-up Study (UM Community Health Sciences), one of the longest-running longitudinal studies in the world. Prior to that, he worked for over a decade as the Faculty of Medicine's IT Coordinator.
Dennis has a B.Sc. (Honors) degree in Computer Science and M.Sc. in Community Health Sciences, both from the University of Manitoba.
He’s a founder and active participant in several Bannatyne Campus community outreach programs: Basketballs for Inner City Kids, SWISH (Summer Weekend Inner-city Supervised Hoops) and the Inner City Kids’ Computer Club.
Research Data Administrator (REDCap Training and Support Lead)
Loring Chuchmach received his M.Sc. in 2002 and has worked at the University of Manitoba since 1996. He joined the Data Science platform at Centre for Healthcare Innovation in 2015 as a data analyst, and prior to this he worked within several departments/faculties at the University of Manitoba including Kinesiology, Sociology, Nursing, and Psychology as both a research assistant and research associate. He has also done analytical contract work for the government of Manitoba. Along with working in the Data Science platform, Loring also holds an appointment in the department of Psychology as a research associate.
Loring has worked on a wide variety of projects, including longitudinal data on older adults (Aging in Manitoba, Successful Aging Projects), academic performance of university students (Motivation and Academic Achievement Study), and administrative health utilization data. Within the data science platform, he works with undergraduates, graduate students, residents, and clinicians to help them plan their projects and work with their collected data. He also provides guidance/instruction on how to manage and analyze data using SPSS.
Josie joined the Data Science Platform, the George & Fay Yee Centre for Healthcare Innovation in 2014. Prior to this, she was an office administrator for 10 years at the Department of Human Genetics, University of Manitoba. She has worked in different Business Units as an administrative assistant at the City of Calgary in 2003 to 2006 and was Digital Media Designer for 5 years at the City of Calgary. She has extensive experience and skills in an office and research environment to provide the research support to the members and trainees of the Data Science Platform.
Research Administrative Coordinator
Brenden Dufault received his MSc in Biostatistics & Epidemiology from the University of Western Ontario in 2009 and has been working as a statistical consultant ever since. He has collaborated with researchers in medicine, dentistry, psychology, nursing, public health, as well as government agencies and the pharmaceutical industry. Although a jack of trades, he specializes in mixed-effects models, latent class and trajectory analysis, and machine learning techniques such as random forests. He is slowly and tortuously transitioning to a Bayesian worldview.
Dr. Depeng Jiang is an Associate Professor in the Department of Community Health Sciences at the University of Manitoba and a lead of the Biostatistics group at the Data Science Platform within the George & Fay Yee Centre for Healthcare Innovation. Dr. Jiang had many years of experience in providing statistical consulting to a broad range of clients and training students and researchers on the conduct of statistical analyses. He is also an Adjunct Professor with OISE of University of Toronto and with Department of Psychology of York University. He also serves as a senior statistical advisor on several organizations (e.g., Child Development Institute, St. Michael’s Hospital).
Dr. Jiang’s program of research focuses on person-oriented statistical methods. His main research interests include longitudinal analysis and multilevel models, person-centered statistical approaches (latent class analysis and growth mixture models), structural equation models, clinical trial design and evaluation. Dr. Jiang is teaching several biostatistics courses in the Department's Graduate Program and currently supervises several graduate students and postdoctoral fellows.
Lead, Biostatistics Group
Dr. Pingzhao Hu received his Master’s degree from Dalhousie University and Ph.D in Computer Science from York University. Prior to joining the George and Fay Yee Centre for Healthcare Innovation, he was working as a research biostatistician and the manager of Statistical Analysis Facility for over ten years at the Centre for Applied Genomics of the Hospital for Sick Children, Toronto.
Currently, Dr. Hu is an Assistant Professor in the Department of Biochemistry and Medical Genetics and Adjunct Professor in the Department of Electrical and Computer Engineering at the University of Manitoba and Assistant Professor (Status) in Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto. His research focuses on statistical genetics and bioinformatics, especially on developing statistical and computational algorithms for integrative analysis of genomic data to understand the causal associations between human genome and phenome. Dr. Hu has published over 80 peer reviewed scientific articles with over 2,500 citations on high-profile journals, such as Cell, Nature Reviews Cancer, Nature Genetics, Plos Biology, Lancet Oncology, Cancer Research, American Journal of Human Genetics, Journal of the American Society of Nephrology, Nucleic Acids Research, etc. He has been supervising graduate students in bioinformatics, genetics, computer science and statistics.
Assistant Professor (Bioinformatics/Statistical Genetics)
Kristine is a Data Analyst in the Data Science Platform mainly working with Manitoba’s administrative data and clinical databases. She leads workshops in R Studio. She completed her B.Sc (Hons) in Statistics and M.Sc in Community Health Sciences both from the University of Manitoba.
Program Coordinator, Visual and Automated Disease Analytics Program
Dr. Wattamon Srisakuldee obtained her Master’s degree and Ph.D from the Department Physiology and Pathophysiology, College of Medicine, at the University of Manitoba. She joined the Data Science Platform of the George & Fay Yee Centre for Healthcare Innovation in July 2016 as a Special Project Advisor. Her work involves the development of Metadata Repository in Manitoba. Prior to this, she was a Research Consultant at the Institute of Cardiovascular Sciences, St. Boniface Hospital Alberchtsen Research Centre, and was a Research Coordinator at the Manitoba Centre for Health Policy, University of Manitoba.
Special Project Advisor
Dr. Rabbani is a biostatistician with the Data Science Platform at the George and Fay Yee Centre for Healthcare Innovation (CHI), as well as an Assistant Professor, Department of Community Health Sciences, University of Manitoba. She has over 10 years of experience in providing statistical consultation, collaboration and training to students and researchers in various specialties. She is an expert on both basic and advanced level of statistical methodologies. She has collaborated and co-authored on several prestigious publications. Her main research interest focuses on Meta-Analysis and Network Meta-Analysis specializing in synthesis projects. Currently she is offering lectures and workshops on meta-analysis in collaboration with the Knowledge Synthesis Platform at CHI. Prior to this position, she had served as a Biostatistician for the Children’s Hospital Research Institute of Manitoba (CHRIM). Dr. Rabbani had previously served as a senior scientist and Assistant Professor at numerous International institutes and Universities in Bangladesh. Dr. Rabbani completed her B.Sc. (Hons) and M.Sc. in Statistics from Jahangir Nagar University, Bangladesh and PhD in Agricultural Economics from Iwate University, Japan.
Dr. Lin Yan joined the George and Fay Yee Centre for Healthcare Innovation (CHI) as a Data Analyst in February 2013. Prior to joining CHI, Lin worked as a Research Analyst with the Saskatchewan Health Quality Council. Lin received a Master's degree in Public Health from the University of Saskatchewan, and a PhD in Pharmaceutics from the Sichuan University in China.
Allison is a current MSc student in the Department of Community Health Sciences at the University of Manitoba and is supervised by Dr. Lisa Lix. She received a BSc (Hons) in Statistics from the University of Manitoba. Throughout her undergraduate studies, Allison was a Student Research Assistant in the Data Science Platform through the Faculty of Science’s Co-op program. She contributed to various statistical consulting projects and workshops.
Naomi is a Research Data Manager in the Data Sciences Platform. Her work involves developing and offering data management strategies for the Data Science Platform that allows researchers to efficiently store, manage, and release data sets to other research team members while ensuring database security and confidentiality. Naomi received her MSc in Kinesiology at the University of Manitoba and her BSc (Hons) at the University of Saskatchewan.
Xuejing is a student on the Data Science Platform of CHI. She joined the team of CHI from May 2018 and worked on the Project 11, evaluation of mental health prevention program. Later in the September, she started her master program in Community Health Science from September 2017 with a concentration on biostatistics under the supervision of Dr. Depeng Jiang.
Yixiu is a data analyst in the CHI team and a master student working with Dr. Jiang in Biostatistics stream at University of Manitoba. She has the basic knowledge in Community Health Science field after finishing all the required courses this year. She also has solid mathematical and statistical knowledge, as well as good teaching skills, as she got her Master’s degree in Mathematics from Hainan Normal University and Bachelor’s degree with the same major from the same university.
Yixiu has basic programming skills of SAS and MATLAB as she has learnt SAS for one year and applied MATLAB as the simulation tool in her master’s thesis.
Sahar Nazari is a Post-Doctoral Fellow in the Data Science Platform at the George & Fay Yee Centre for Healthcare Innovation, University of Manitoba. She completed her PhD in Statistics at Shiraz University, Shiraz, Iran and during her PhD, she visited Department of Statistics, University of Manitoba, as a visiting PhD student. Her PhD research was mainly focused on Nonparametric inferences under the rank-based sampling designs. A key focus of Sahar's post-doctoral research will be to work on person-oriented statistical methods.
Stephanie is a Research Assistant for supervisor Dr. Lisa Lix in the Data Sciences Platform. She has been involved in many projects throughout her time at CHI, first starting as a summer student in 2016. Stephanie has received her BSc (4yr) in Statistics at the University of Winnipeg and is currently working towards her MSc in Community Health Sciences with a Concentration in Biostatistics at the University of Manitoba.
Graduate Student; Research Assistant
Marcello Nesca has a diverse background with a focus on Research. Graduating with a B.Com (Hons) in 2005, he has worked in the telecommunications industry for close to 10 years with 8 of those years spent as a research analyst, business analyst, and a database analyst. After shifting gears, he has decided to enter the social sciences and acquire a B.A (Hons) in Psychology with a thesis in quantitative methods. Now, in the MSc program in Community Health Sciences, Marcello will specialize in Data Science and Statistics under the supervision of Dr Lisa Lix. His thesis focuses on finding tools to assess the quality of unstructured text data in electronic health databases. Concurrently with the MSc program, he is a student in the VADA program. His current research interests in quantitative methods are: Data quality, data visualization, data automation, Robust Statistics, and Structural equation modelling. Furthermore, he is interested in Knowledge Translation, in particular to quantitative methods, and Quantitative evaluation of programs/policy/process. Aside from academia, Marcello enjoys cooking, staying active, camping, and going out with friends and family.
Justin received his B.Sc. in statistics from the University of Winnipeg in 2017 and is currently a M.Sc. student in the department of Community Health Sciences at the University of Manitoba under the supervision of Dr. Mahmoud Torabi. His current research interests include spatial statistics and spatio-temporal modelling, where his M.Sc. thesis is a population based spatial analysis study. Previously Justin has worked at the tutoring centre at the University of Winnipeg tutoring students in Statistics courses, and at Manitoba Health as a statistical analyst.