Biostatistics
Service

In addition to offering bioinformatics support for analysis of omics data, we also offer biostatistics support for analysis of cohort and experimental data. We can assist with the following aspects as required:

• Experimental design, including formulation of hypotheses, sample size calculations and randomisation
• Quality control and cleaning of datasets for downstream analyses
• Descriptive statistics, exploratory data analysis and plots
• Basic statistical analysis including t-tests, ANOVA, correlation and contingency table methods
• Statistical modelling of numerical and binary outcomes using linear or logistic regression
• Statistical modelling of rates and survival times using Poisson regression or survival analysis
• Analysis of clustered or longitudinal data using robust standard errors, random effects models or generalised estimating equations
• Development of clinical prediction models using statistical modelling or machine learning approaches 
• Dose-response modelling
• Dimensionality reduction techniques to discover underlying patterns in datasets
• Regular meetings to discuss interim results
• Fully detailed report showing all analysis code
• Interpretation of results
• Publication quality figures and writing of relevant sections of manuscript
• Assistance with writing of grant funding applications