YHTTAY-24486 High-throughput Data Analysis, 5 cr
Additional information
http://bioinformatics.fi/BIO4450/
The course is only intended for degree students
Person responsible
Matti Nykter
Lessons
| Implementation | Period | Person responsible | Requirements |
| YHTTAY-24486 2018-01 | 4 |
Matti Nykter |
Learning Outcomes
After the course, the student can: - compare sequencing and microarray technologies used in high-throughput analysis and choose suitable ones for the analysis required. - explain the principles of measurement technologies covered and how various inherent errors and biases of the measurement techniques affect the analysis. - apply common methods and algorithms to extract information from microarray and sequencing measurements. - discuss the statistical principles underlying the data analysis methods above and identify the benefits and weaknesses of each method. - select suitable algorithms for the analysis and justify the choice. - build data analysis pipelines for microarray and sequencing data analysis.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Deep sequencing technologies DNA microarrays Statistical methods for the analysis of high-throughput measurement data Data classification and clustering |
Correspondence of content
| Course | Corresponds course | Description |
| YHTTAY-24486 High-throughput Data Analysis, 5 cr | YHTTAY-24487 Introduction to High-Throughput Data Analysis, 5 cr |