| CODE | SOR2520 | ||||||||||||||||
| TITLE | Statistics in Bioinformatics | ||||||||||||||||
| UM LEVEL | 02 - Years 2, 3 in Modular Undergraduate Course | ||||||||||||||||
| MQF LEVEL | 5 | ||||||||||||||||
| ECTS CREDITS | 5 | ||||||||||||||||
| DEPARTMENT | Statistics and Operations Research | ||||||||||||||||
| DESCRIPTION | The aim of this study-unit is to provide a basic introduction to core statistical concepts and methods thus providing a sound framework for the application of statistical methods in genomics. The first part of the unit will cover the following fundamental topics: (1) Introduction to Probabilistic and Statistical concepts; (2) Data Exploration and Visualisation using R - looking at the most common statistical and visual techniques for preliminary data analysis; (3) Basics of Sampling - introducing fundamental concepts on sampling, including important tools such as margin of error, sample size calculation and power of the test; (4) Tests for correlation, association and comparison of means - parametric and non-parametric tests, when and how to implement them using R; (5) Post-hoc analysis when comparing more than two samples. In the second part, more advanced topics shall be covered. The detail in which the following topics will be covered will depend on the background of the students following the course in the particular year: (6) Statistical modeling, e.g. regression analysis, generalized linear models; (7) Multivariate analysis, e.g. principal component analysis; (8) Experimental design - introducing the concept, how to deal with nuisance variables and confounding; (9) Introduction to regularization techniques: such as Partial Least Squares, LASSO and RIDGE; (10) Interpreting Bayesian statistics: an introduction. Study-unit Aims: The primary objective of this study-unit is to equip students with the essential mathematical and statistical foundation necessary for conducting postgraduate research in bioinformatics. The unit will illustrate and examine real-world examples from bioinformatics, explaining the underlying statistical theories through the application of various statistical tests. Each test will be demonstrated to show how it can lead to specific conclusions when analysing particular data sets, highlighting the importance of selecting the most appropriate test. Correct interpretation of software output is crucial, enabling students to draw meaningful conclusions from the data analysed. Learning Outcomes: 1. Knowledge & Understanding By the end of the study-unit the student will be able to: - Identify the correct statistical tests to analyse a data set; - Implement statistical tests using software; - Interpret the output obtained from software output and draw the correct conclusion; - Provide a written report which contains a thorough analysis of a data set; - Use R programming language to implement the statistical methods discussed. 2. Skills By the end of the study-unit the student will be able to: - Learn to program statistical concepts in R; - Create visualisations to present biological data; - Decide which statistical method/s are the most appropriate to use for the analysis of a specific data set, whilst taking into consideration assumptions of the test and type of data; - Report scientific findings in a sound statistical manner; - Give a presentation on statistical techniques with relevance to the field of bioinformatics. Main Text/s and any supplementary readings: Main Texts: - Field, A. and Miles, J. (2012). Discovering Statistics using R. Sage Publishing. - Lambert, B. (2018). A Student's Guide to Bayesian Statistics. Sage Publishing. - Sunil, K. M. (2009). Statistical Bioinformatics with R. Academic Press. - Sinha, P. P. (2014). Bioinformatics with R Cookbook. Packt Publishing. - Nature Collection - Statistics for Biologists. https://www.nature.com/collections/qghhqm Supplementary Readings: - Spiegelhalter, D. (2019) The Art of Statistics: Learning from Data, Pelican. |
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| STUDY-UNIT TYPE | Lecture | ||||||||||||||||
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| LECTURER/S | Monique Borg Inguanez Derya Karagoz Fiona Sammut |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
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