R is currently perhaps the most powerful and widely used tool for calculations of all kinds. A wide range of modules for working with molecular data is also available. A representative selection of these modules is the focus of this course.
The course includes theory on the methods used, tutorials using test data, assignments for independent work by participants, and more. The goal is to teach students how to analyze molecular data using the R programming language, introduce available packages for such analysis, and provide hands-on experience analyzing their own or provided data.
Prior knowledge of R is an advantage but not a requirement. At least a basic understanding of molecular biology is necessary, and prior knowledge of at least some methods for analyzing DNA data is recommended. The course is more suitable for master’s and doctoral students; it is suitable for bachelor’s students only if they are very advanced.
The course will be held in a 5-day session.
Information is continuously updated in SIS. Schedules are also in SIS. The course will be taught in lecture hall OŽP B12 (1st mezzanine, Benátská 2, Prague 2) from February 2 to 5, 2026, from 9:00 AM to ca. 3:30 PM (with enough breaks). I'd be glad if participants could fill a short questionnaire which will help me with preparation of the course and communication with participants.
The course will be a combination of shorter talks, followed by independent work of students, and room for questions, consultations, etc. Details will be updated according to the situation prior the course.
Syllabus
Preliminary overview of topics and schedule (subject to change based on participants’ requests, pace, etc.):
Day 1
- Basics of working in R, installing packages.
- Importing and exporting molecular data of various types and formats (microsatellites, VCF, sequencing data, etc.).
- Downloading sequences from a database.
- Extracting SNPs from sequencing data.
- Alignment.
- Data manipulation, conversion between formats.
- Creating distance matrices, importing custom matrices.
Day 2
- Population genetics and genomics: basic statistics, genetic indices, heterozygosity, HWE, F-statistic, PCoA, NJ, MSN.
Day 3
- DAPC.
- Spatial analyses—Mantel test, Moran’s I, Monmonier, sPCA, …
- Basics of map creation.
Day 4
- Tree manipulation, processing large numbers of trees.
- Phylogenetic independent contrast.
- Phylogenetic autocorrelation.
- Phylogenetic PCA.
- Ancestral state reconstruction.
Day 5
- Graphics.
- GitHub.
- Scripts, loops, and conditions.
- R at MetaCentrum.
Time for additional specific questions from participants, assessments, and consultations on participants’ own data will be allocated primarily during the last day.
For course you need own computer to work and installed R. I also recommend to install some graphical user interface like RStudio, RKWard, R commander or some similar according to your choice. If you have experience with R, you can save some work by installing required R packages in advance. I'll send instructions prior to the course. If you do not wish to install everything, you can use prepared Linux image for VirtualBox containing everything needed.
