The statistical genetics team was established in 2004 at the Montreal Heart Institute by Dr Dubé, and the team has unique expertise in the conduct of statistical analyses and epidemiological studies with genomic data. The statistical genetics core provides expertise at all stages of the PGx Centre’s projects, by working interactively with the users.
Statistical considerations in pharmacogenomic studies are important as hypotheses and conclusions arising from such studies need to be supported with credible data in order to lead to the rapid translation of findings. We promote the use of study designs that avoid or mitigate confounding from technical variations and patient variations. Tests of the reproducibility of genetic findings are planned and integrated into projects.
Projects are designed in accordance with regulatory recommendations by health authorities to allow for rapid and unambiguous decision making. When appropriate, study designs will enable the evaluation of the classifier performance of a discovered genetic marker, its predictive attributes and quantitative characteristics.
Statistical analysis plans (SAP) are prepared in collaboration with the users. SAPs are approved in the early stages of the projects to streamline the analysis steps when genomic data become available. SAPs include the study rationale and hypotheses, study methodologies, specific study objectives, specific analytical sets, step-by-step analytical processes, planned sensitivity analyses, subgroup analyses, result tables, and the planned reported statistics and documentation. When appropriate, SAS code is developed and validated prior to data reception which can efficiently accelerate statistical reporting. Quality check procedures are implemented in the planned processes as part of the analyses. The statistical team provides feedback to researchers at pre-specified steps in the analytical process to validate the concordance of data and results with reasonable expectations.
Methodological rigour and traceability are central to reporting practices in place at the PGx Centre. Comprehensive statistical analysis reports document clearly the statistical results, the underlying model assumption(s) and methods used in accordance with the SAP and ensure accurate interpretation of the results by the users. Reports include transparent information on methodology and findings which allow for the conduct of rapid and accurate reviews by peers and regulatory agencies.