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FEKT-MPAN-PMBAcad. year: 2026/2027
The course is mainly oriented towards acquiring practical skills in the field of bioinformatics processing of big data. It mainly focuses on analyses of bacterial genomes and transcriptomes. For the complexity of such analyses, it also brings a basic understanding of working with the command line, creating your own pipelines and using remote calculations. All this while understanding how these analyzes are applicable to the knowledge inference that can be used in medicine, biotechnology or genome engineering. Current bioinformatics processes big data that cannot be processed on personal computers. Therefore, it relies on remote calculations on high performance computational servers. This requires the use of a job scheduler and, in cooperation with basic code scripting, gives almost unlimited possibilities even in the analysis of so-called non-model organisms. Computational analyses can thus be used in many scientific disciplines, especially biotechnology, both medical and industrial.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
It is required to have basic knowledge of algorithms used in bioinformatics for sequence similarity analysis, assembly into longer sequences, or algorithms deriving information from primary sequence structure, such as ORF prediction. It is also important to have a basic understanding of functional relationships in living organisms at the cellular level based on the central dogma of molecular biology.
Rules for evaluation and completion of the course
Criteria for obtaining classified credit:
- prepare a report summarizing your own results on all topics assigned during the semester (max. 100 points)
Computer exercises and semminars are not mandatory, absences do not need to be compensated. To successfully complete the course, it is necessary to obtain at least 50 points for the final report. The finals score is determined from the points obtained for the final report.
Aims
The aim of the course is to provide students with advanced, practically oriented knowledge in the field of sequencing data processing using batch jobs and high-performance computing with modern computing tools so that they are able to set up their own pipelines for complex genome analyses. The graduate of the course is able to: - work with computing resources using batch jobs while using a scheduler- perform quality assessment of raw sequencing data, both genomic and transcriptomic- assemble a complete genome and annotate it- perform variant calling in mutant or otherwise related genomes- perform a comprehensive analysis of the transcriptome
Study aids
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
Seminar
Teacher / Lecturer
Syllabus
1. Introduction to high performance computing2. Contamination and sequencing errors, genome assembly 3. Population genomics and variability in genomes 4. Basics of structural and functional genome annotation 5. Basics in transcriptomics6. Analyses of transcriptomes
Project
Work on assigned tasks necessary for the preparation of the final report. It is required to work on all assigned topics.
Individual preparation for an ending of the course
Requirements for the final report
The final report does not have a precisely defined structure, it is possible to freely draw inspiration from scientific articles, project reports, or even bachelor/diploma theses. The report should contain:
1) IntroductionA brief introduction to the state-of-the-art, a general description of the topic and a 2-3 sentence summary of what the report contains.
2) Materials and methodsThis chapter should contain references to the input data, where they were obtained, including accession numbers, computational tools used, including specific versions and any references, in case a freely available tool needs to be cited.
3) Description and discussion of resultsThe achieved results, including suitable figures, plots and tables, should be summarized in a separate chapter. This can be divided into further subchapters reflecting individual topics addressed during the semester. The results can be directly discussed, or the discussion can be placed into a separate chapter.
4) Conclusion/summaryThe report should also include a brief summary of everything that was successful, or failed.
Exercise in computer lab
1. Metacentrum, sratoolkit, quality assessment for raw sequencing data 2. Quality trimming and data preparation, de novo genome assembly3. Reference-based assembly, variant calling4. Genome annotation5. RNA-Seq preprocessing, mapping, demultiplication6. RNA-Seq – count table7. Consultations