| Course title | Courses of work with molecular data in R |
|---|---|
| Course code | KBO/148 |
| Organizational form of instruction | Lesson |
| Level of course | Doctoral |
| Year of study | not specified |
| Frequency of the course | In academic years starting with an even year (e.g. 2024/2025), in the winter semester. |
| Semester | Winter |
| Number of ECTS credits | 4 |
| Language of instruction | English |
| Status of course | Compulsory-optional |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Course availability | The course is available to visiting students |
| Lecturer(s) |
|---|
|
| Course content |
|
Content of practicals: Basic methods of work R programming language, theory of methods used (there are short lectures before every practical session) Basic work in R - how to enter commands, install packages, read help, types of variables, indexes, etc.; Bioconductor; Load and export molecular data of various types and formats; Download molecular data from on-line databases; Extractions of SNP from sequencing data; Extraction of polymorphism from sequences; Mikrosatellites, AFLP, SNP, sequences, ?; Manipulations with data, conversions among formats; Distance matrices, import of custom matrices; Export of data; Basic statistics; PCoA; Phylogenetic trees (NJ, UPGMA, ML) and display and test; MSN; Basic statistics, genetic indices heterozygosity, HWE, F-statistics; DAPC; Whole genome SNP data; Spatial analysis - Mantel test, Moran's I, Monmonier, sPCA, ?; Basic map creation; Structure; Alignments; Manipulations with trees, work with big sets of trees; Phylogenetic independent contrast; Phylogenetic autocorrelation; Phylogenetic PCA; Ancestral state reconstruction; Additional extending topics?
|
| Learning activities and teaching methods |
Activating (simulations, games, drama)
|
| Learning outcomes |
|
To teach students analysis of molecular data in R programming language, introduce packages available for analysis of molecular data. Practical work, analyzing of own or provided data.
|
| Prerequisites |
|
unspecified
|
| Assessment methods and criteria |
|
Interim evaluation
|
| Recommended literature |
|
| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester |
|---|