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.
Contents
Deep sequencing technologies DNA microarrays Statistical methods for the analysis of high-throughput measurement data Data classification and clustering
Modes of study
Option
1
Available for:
Degree Programme Students
Other Students
Open University Students
Doctoral Students
Exchange Students
Participation in course work
In
English
Exercise(s)
In
English
Lectures 20 h Independent work 14 h Independent work by following the provided instructions