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Information for module GENEG005

This module is available for 2017/18

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Module code:GENEG005 (Add to my personalised list)
Title:Statistics for Interpreting Genetic Data
Credit value:15
Division:Division of Biosciences
Module organiser (provisional):Dr Maria Secrier and Dr Elvira Mambetisaeva
Organiser's location:Darwin Building
Available for students in Year(s):
Module prerequisites:Available to Masters students only 
Module outline:The module will provide an introduction to computer-based statistical methods of analyzing and interpreting genetics data. The topics to be covered include: population genetics (both forward-in-time and backward-in-time models); the study of disease transmission in families (twin studies, segregation and linkage analysis); genetic epidemiology; Mendelian randomization; genetic association studies; genome-wide analyses; fine mapping; the effects on association analyses of admixture and population stratification; sequencing technologies, variant calling methods and biases; phylogenetic reconstruction of cancer lineages. The emphasis will be on students doing analyses in class, in groups, and on their own, and on their 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, knowledge of fundamental concepts in probability and statistics (e.g.statistical distributions, Bayes theorem etc.), and a good understanding of the following biological concepts: DNA, gene, protein, chromosome, species, phylogenetic tree, Mendelian genetics, basics of human genetics, basics of DNA 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 statistical techniques applied in genetics and genetic epidemiology.  
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 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 data analysis. Interpretation of results from statistical analysis of genetic data. 
Module timetable: 
Module assessment:Unseen two-hour written examination 60.00%
Four computer-based assignments 40.00% 
Taking this module as an option?: 
Link to virtual learning environment (registered students only)
Last updated:2017-11-22 11:24:37 by ucbtecr