PHM5003 – Applied Statistics for Precision Medicine
Course Overview
Precision medicine leverages on insights derived from the analysis of high-throughput datasets containing multiple parameters. This module aims to provide foundational knowledge and skills for students to apply appropriate statistical approaches in evaluating and analysing high-throughput datasets in precision medicine. Students will develop the skills in designing experiments based on the statistical principles, evaluating data quality, analysing and interpreting high throughput data for precision medicine.
Learning Outcomes
At the end of this course, students will be able to
- Explain principles of statistical modelling of data for precision medicine
- Explain the challenges of analyzing high throughput datasets for precision medicine
- Design high throughput experiments in precision medicine to minimize confounders and increase statistical power to detect differences
- Evaluate data quality (batch effects, missing data, noise) and perform preprocessing where appropriate (batch correction, imputation, normalization)
- Analyze high throughput data to find and evaluate differences in samples using appropriate statistical tools
Course Outline
- Overview of R/Bioconductor
- Overview of basic statistics
- Challenges with datasets in precision medicine
- Statistical principles for high throughput data in precision medicine
- Case studies of analysis in precision medicine
Course Requirements
Basic knowledge of R programming language