CAMBRIDGEGENOMIC MEDICINE

GM2 · MPHIL & MRES · 2026–27

Research and statistical skills for genomic medicine

Previously: Research and statistical skills. About the module name changes

About this module

This module aims to provide and equip students with the knowledge of statistics and computational tools needed to independently complete genomic medicine research. This module complements the knowledge from the wider course to ensure all students are competent in planning research, and can perform appropriate statistical analysis in R. The module is designed to prepare students for research projects and presents material in this context. This module serves as an informatics foundation for students learning bioinformatics and statistical languages. The module provides both self-directed and supervised learning of the R statistics language. This module provides a foundation for performing a research project and for students considering undertaking a PhD in future years.

15 credits · Module Leads: Dr Tim Hearn (University of Cambridge) and Dr Leonardo Bottolo (University of Cambridge)

Before the module

Suggested preparation

Module-specific materials and instructions are provided through your course Moodle/VLE. These refreshers are optional support, not additional assessment requirements.

What you will study

  • How to write a research grant proposal
  • Up to date computational and experimental tools for genomic medicine research projects
  • Fundamental concepts in statistics offering students a foundation and framework for understanding more complex methods.
  • Implementation of the statistical methods illustrated during the course using the R environment.
  • Basic concepts in using R
  • Basic statistical and mathematical concepts including correlation, regression, model selection, and generalized linear models
  • Exploration of Bayesian statistics and tools applied for haplotype estimation and Machine Learning tools for non-linear regression will also be explored

Learning objectives

By the end of this module you will be able to:

  • Demonstrate a rounded knowledge of the classic and modern tools and technologies used in research projects. Emphasis will be placed on the overlap between modern and traditional approaches and the type of data they might be presented within a research project
  • Understand the conceptual basis for statistical tests, and be aware of the various tools that they can implement when exploring either genomic or expression data
  • Choose the correct statistical test based on the data source and experimental design and implement the test in R

Teaching

20, 23, 29 October; 5, 19, 26 November 2026; optional 10 December

School of Clinical Medicine, Hills Road, Cambridge CB2 0QQ

Dates follow the 2026–27 handbook. Check your course communications for timetable updates.

Learning objectives follow the 2026–27 curriculum, including programme-team updates.