Přístupnostní navigace
E-application
Search Search Close
Course detail
FEKT-MPC-PMBAcad. year: 2024/2025
The course is mainly oriented towards acquiring practical skills in the field of bioinformatics processing of large datasets. It mainly focuses on analyzes 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 large amounts of data that cannot be processed on personal computers. Therefore, it relies on remote calculations on powerful computational servers. This requires the use of a task scheduler and, in cooperation with basic code scripting, gives almost unlimited possibilities even in the analysis of so-called non-model organisms. Computational analyzes can thus be used with great overlap in many scientific disciplines, especially biotechnology, both medical and industrial.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
A student enrolled in this course should be familiar with the principles of algorithms used in bioinformatics for the analysis of sequence similarity, their assembly into longer sections, or algorithms deriving information from the primary structure of the sequence. They must also understand the basic functionality of organisms at the cellular level based on the central dogma of molecular biology.
Aims
The aim of the course is to provide students with advanced knowledge in the field of sequencing data processing through batch jobs and cloud computing using modern computational tools so they are able to set up their own pipelines for complex genome analysis.
A graduate of the course is able to:
- to work with computing resources using batch jobs while using the scheduler
- to perform quality assessment of both genomic and transcriptomic sequencing data
- to assemble the complete genome and annotate it
- to call variants in mutant or otherwise related genomes
- to perform an in-depth analysis of the transcriptome
Study aids
Prerequisites and corequisites
Basic literature
Recommended literature
Classification of course in study plans
Exercise in computer lab
Teacher / Lecturer
Syllabus
1. Introduction, metacentrum, sratoolkit, sequencing data quality assesment
2. Trimming, de novo assembly
3. Reference-based assembly, variant calling
4. Genome annotation
5. RNA-Seq preprocessing, mapping
6. RNA-Seq – count table