Module Database

Information for module GENE0005

This module is available for 2019/20

If you're a member of UCL you can add this module to your personalised course list

This information is for guidance only. If you are an UCL undergraduate interested in studying one of these courses, you must seek permission from both the providing department and your 'home' department. Appearance in this database is not a guarantee that a course is running in any particular academic year.

Module code:GENE0005 (Add to my personalised list)
Title:Advanced Computational Biology
Credit value:15
Division:Division of Biosciences
Module organiser (provisional):Dr Maria Secrier
Organiser's location:Darwin Building, room 218A
Available for students in Year(s):
Module prerequisites:Available to Masters students only 
Module outline:The module will provide an introduction to statistical and computational methods of analyzing and interpreting genetics/genomics data. The topics to be covered include: contemporary approaches to NGS data analysis (read quality assessment, genome alignment, comparative genomics); gene expression variation (differential expression analysis of RNA-Seq data); association studies (GWAS, eQTL); population genetics (both forward-in-time and backward-in-time models); species tree estimation using the multispecies coalescent; Bayesian computation and Markov Chain Monte Carlo (MCMC) methods applied to comparative genomics; phylogenetic reconstruction of cancer lineages. The emphasis will be on students doing analyses in class, and on the interpretation of the results. Programming will form a major part of this course. Students will learn how to write their own scripts to perform advanced statistical analyses of genetic data. No previous programming experience is required, but students should have an interest in developing such skills. All students wishing to enrol in this course should have good numeracy skills, in-depth knowledge of fundamental concepts in probability and statistics (e.g.statistical distributions, probability theory, Bayes theorem etc.), calculus, matrix algebra, and a good understanding of fundamental genetics/biology concepts: DNA, gene, protein, chromosome, species, phylogenetic tree, Mendelian genetics, basics of human genetics, DNA/RNA sequencing. For people without a biological background, we recommend the following books: Principles of Genetics. 7th edition. D.P. Snustad and M.J. Simmons (2015) Wiley; Human Molecular Genetics 4. T. Strachan & A. Read (2011) Garland Science; Human Genes and Genomes: Science, Health, Society L.E. Rosenberg & D.D. Rosenberg (2012) Academic Press. 
Module aims:To provide an introduction to computational and statistical techniques applied in genetics and genomics.  
Module objectives:An understanding of the rationale underlying standard computational statistics procedures, and the situations in which different procedures are applicable. The ability to use computational and statistical techniques to analyse genetic data, particularly to understand the role of genetics in disease causation. The ability to interpret the results of statistical analyses.  
Key skills provided by module:Programming in R. Understanding and implementing a wide range of statistical techniques for genetic/genomic data analysis. Interpretation of results from statistical analysis of genetic data. 
Module timetable: 
Module assessment:

PG FHEQ Level 7

  • Standard assessment pattern:
    • Four computer-based assignments 40.00%
    • Unseen two-hour written examination 60.00%

UG FHEQ Level 7

  • Standard assessment pattern:
    • Four computer-based assignments 40.00%
    • Unseen two-hour written examination 60.00%
Taking this module as an option?: 
Link to virtual learning environment (registered students only)
Last updated:2018-10-11 14:32:23 by ucbtecr