Programming for biologists

Programming iconCourse code: RSDA6005 (Book on MyCampus)

RDF domain: A1.3, A1.5, A1.7

Speaker: Mrs Karen Lennie and Mr Euan Fulton, IT Services

Target group: All postgraduate research students and postdoctoral researchers

Credit: 1

Description: This course, run over three half-days, provides a brief introduction to computer programming with emphasis on biological data analysis. It is aimed at those with little or no prior programming experience, but a general level of computing proficiency will be required. On successful completion of this course participants will have:

  • learned to write their own simple programs and to use/adapt programs written by others.
  • insight into when programming should be used in analysing biological data.
  • experience of the fundamentals of programming: variables, loops, control statements and working with files.
  • extracted and processed information from spreadsheet files, i.e. Excel.
  • understanding of some example programs working with DNA sequences.
  • knowledge of other available resources and how to progress further.


  1. A short course such as this cannot make you an expert programmer. Rather, the course aims to give you a taster of  programming tools available for biology and how programming can be useful to you in your research.
  2. Your feedback on how the course might be improved will be much appreciated.

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More advanced uses of R

Programming iconCourse code: RSDA6014

RDF domain: A1.1, A1.2

Speaker: Professor Adrian W Bowman, School of Mathematics & Statistics

Target group: Research students and postdoctoral researchers who have introductory-level knowledge of R, including those who have attended the ‘What is R?’ session

Credits: 2

Description: The aim of the session is to explore some of the more advanced aspects of R as a statistical computing environment.

Participants will be invited to express interest in particular topics and this will have an influence on those chosen as the focus of the session. Possibilities include random effect models, flexible regression models, spatial analysis and the use of R as a programming environment. There may be an opportunity for participants to bring their own data, depending on the size of the group.

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R for research (5 two hour sessions)

Programming iconCourse code: RSDA6184 (Book through MyCampus)

RDF domain: A1.1, A1.2

Speaker: Mr Jesus Rodriguez Perez, Institute of Health & Wellbeing

Target group: Postgraduate research students, postdoctoral researchers, and staff on a research related role utilising R as the main analysis language

Credits: 3

Description: This course will cover the necessary material to effectively use the R programming language and related packages towards producing quality research. The course will begin with an introduction to standard R for those unfamiliar with the scripting language and most commonly used libraries. Furthermore, we will learn about version control, and how to effectively keep and organise snapshots of your work through time in semi-automated manner.

Subsequently, students will learn about streamlining the creation of quality research papers utilising Rmarkdown. Amongst other benefits, Rmarkdown helps bringing data into documents in a semi-automated way. Finally, students will also learn about creating simple dynamic web applications where to present their research results utilising RShiny.

Students with any level of programming proficiency are encouraged to join the course, as we will be very light in terms of coding and focus on basic understanding of the tools available. The only requirement is to have an interest in the R ecosystem and the ways it can enhance their research. In exchange you will be empowered with a set of tools, that will make your future work more reproducible, organised, and interactive.

We will reserve time every session for questions, and assistance in completing and understanding the exercises, and making sure people get a valuable and useful experience out of this course.

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What is R?

Programming iconCourse code: RSDA6013 (Book through MyCampus)

RDF domain: A1.1, A1.2

Speaker: Professor Adrian W Bowman, School of Mathematics & Statistics

Target group: All postgraduate research students and postdoctoral researchers who wish to develop their skills in the field of data analysis

Credits: 2

Description: R is an open source statistical computing system which has facilities for a very wide range of statistical methods but which is also a very flexible programming environment. There is now a very large user community and a considerable collection of additional libraries available for specialist topics. This short course aims to provide a broad introduction to the system. The topics covered will include:

  • facilities for standard analyses
  • graphics
  • linear models
  • multivariate methods

The course will be based around a small number of case studies and there will be an opportunity for practical use of the system. The very wide range of facilities offered by the R environment will be outlined.

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