Linux (and another software)

R is nowadays probably the most powerful tool for calculations of all kinds. There are plenty of modules available for work with molecular data. Their representative selection will be introduced during the course.

The course contains theory of used methods, tutorials with test data, tasks for individual work of participants, and more. The aim is to teach students how to analyze molecular data in R programming language, introduce available packages for their analysis and practical trying out to work with own or provided data.

Don’t be afraid of command line! It is friendly and powerful tool allowing to process large data and automate tasks. Practically identical is command line also in Apple macOS, BSD and another UNIX-based systems, not only in Linux. The course is designed for total beginners as well as intermediate advanced students. The only requirement is an interest (or need) to work in command line, typically on Linux computing server.

Custom probe design for target enrichment in phylogenetics is tedious and often hinders broader phylogenetic synthesis. The universal angiosperm probe set Angiosperms353 may be the solution. Here, we test the relative performance of Angiosperms353 on the Rosaceae subtribe Malinae in comparison with custom probes that we specifically designed for this clade. We then address the impact of bioinformatically altering the performance of Angiosperms353 by replacing the original probe sequences with orthologs extracted from the Malus domestica genome.

Set of scripts to run STRUCTURE in parallel on computing grids like MetaCentrum. Scripts are designed for grids and clusters using PBS Pro, but can be easily adopted for another queue system.

R is nowadays probably the most powerful tool for calculations of all kinds. There are plenty of modules available for work with molecular data. Those will be introduced during the course.

The course contains theory of used methods, tutorials with test data, tasks for individual work of participants, and more.

Previous knowledge of R is useful, but not necessary. At least basic knowledge of molecular biology is required, previous knowledge about any methods how to analyse DNA data is recommended.

Don’t be afraid of command line! It is friendly and powerful tool allowing to process large data and automate tasks. Practically identical is command line also in Apple macOS, BSD and another UNIX-based systems, not only in Linux. The course is designed for total beginners as well as intermediate advanced students. The only requirement is an interest (or need) to work in command line, typically on Linux computing server.

Course will be taught in Linux, but most of the point are applicable also for another UNIX systems like macOS.

R is nowadays probably the most powerful tool for calculations of all kinds. There are plenty of modules available for work with molecular data. Those will be introduced during the course. The course will be taught from October 19^th to Friday 23^rd (see below). The course will be exclusively on-line, there will be no personal meeting.

Intensive 4-days (5^th day is not compulsory, but is open for any discussion, if there would be interest) course to learn all theory about HybSeq and practically learn how to analyze HybSeq data, how to solve all problems, and how to evaluate differences among gene trees. Important part is enough time to discuss everything, including practical problems and projects of individual participants.

Don’t be afraid of command line! It is friendly and powerful tool allowing to process large data and automate tasks. Practically identical is command line also in Apple osX, BSD and another UNIX-based systems, not only in Linux. The course is designed for total beginners as well as intermediate advanced students. The only requirement is an interest (or need) to work in command line, typically on Linux computing server.

Course will be taught in Linux, but most of the point are applicable also for another UNIX systems like osX.

R is nowadays probably the most powerful tool for calculations of all kinds. There are plenty of modules available for work with molecular data. Those will be introduced during the course.

The course contains theory of used methods, tutorials with test data, tasks for individual work of participants, and more.

Previous knowledge of R is useful, but not necessary. At least basic knowledge of molecular biology is required, previous knowledge about any methods how to analyse DNA data is recommended.