The course aims to provide a view and practical knowledge of data downloading, handling, processing, and visualization methods of various high-throughput experiments. The most important topics of the practical: (1) Introduction to the computer environment, bash, and workflow management, (2) Introduction to next-generation sequencing in general, (3) Genomics, (4) Chip-seq, (5) Transcriptomics (RNA-seq), (6) Functional enrichment analysis, (7) Marker gene amplification metagenomics (16S rRNA), and (8) Proteomics.
The most up-to-date schedule, detailed description, and requirements can be found here:Â https://docs.google.com/document/d/1z0–wXp5lenl1WI-p8CLCsZRuaJbkdgog1cmJpR7wlg/edit?usp=sharing
At the end of the course, the learner will have this knowledge:
Knows how to process high-throughput genetics and proteomics data.
Understands the next-generation sequencing methods, data, and how to process the “reads” in the case of genomic, Chip-seq, RNA-seq, and 16S rRNA metagenomics sequencing.
Knows the fields of application of modern biological research methods, understands the importance of the development of these methods, and contributes to it as much as possible.
Has systematic scientific knowledge.
Knows the connections between the knowledge acquired in different subjects, and understands the importance of an interdisciplinary approach.
At the end of the course, the learner will be able to:
– express oneself professionally, both in oral and written form, in the field of bioinformatics, high-throughput genetics, and proteomics.
– systematize data and knowledge, and analyse and evaluate them according to scientific aspects.
– recognize and integrate connections between the knowledge of different scientific fields.
Attitude:
Adheres to and makes others follow the rules of research ethics.
Actively disseminates the results of the field of science, confidently publishes knowledge even in the media, and defends his/her professional position against representatives of other approaches and pseudoscience, if necessary.
Open to new biological and other scientific research results and scientific cooperation. Seeks to further develop existing results and actively promotes the development of new research directions.
Committed to quality work, sets a high standard for the scientific knowledge and advancement of himself and fellow researchers.
Autonomy and responsibility:
Expresses views on biological, bioinformatics, and high-throughput method issues responsibly in professional and non-professional circles.
Maintains a modern computer environment and helps with continuous methodological and technological renewal in order to work as efficiently as possi
Weekly grades
You will receive a grade for your work weekly. The mean of the weekly grades will make up half of your final grade.
Students may miss up to 3 practicals. This means that you won’t receive a grade for that week, nor will it count toward your final grade.
Project work for the exam
Each of you has to choose an OMICS data set to analyse using the methods you’ve learned in the course. So you can do proteomics, SNP analysis, RNA-seq, ChIP-seq analysis, etc. It is up to you to decide what kind of analysis you will perform. Do not hesitate to contact the instructors if you need assistance choosing a topic or data set(s). If you decide what dataset to use and what analyses to conduct, please write 3-4 sentences by TBA date here: TBA. By TBA date, the instructors will determine whether the promoted topic and dataset are appropriate for the project work.
Following that, you perform the analysis on your own. Ensure that every step is reproducible by creating a log file or a report. Prepare a 10-minute presentation with slides that describe the data set, the analysis, and the results. Send the log file or analysis report by email to the instructors by TBA date.
Present your work to the instructors and peers on TBA date(s) during the practical. The instructors and peers may ask questions about the analysis you presented.
The final practical grade is based on your work throughout the semester (50%) and your presentation (50%). You must obtain at minimum a grade 2 for both your overall semester work and your analysis and presentation in order to successfully complete this course.
Recommended literature, papers, and websites will be provided at the end of each lecture.
Lectures, demonstration, practical: individual work on computers, presentation of the results.
Transcript of records