Spring Session Graduate Course on Transcriptomic Data Analysis: Applied Bioinformatics Concepts for Life Science Research led by Dr. Gus Kousoulas, Dr. Ramesh Subramania, Dr. Lyndon Coghill, Chris Taylor, and Urska Svek. In this course, we will explore how gene expression can be studied using high throughput sequencing data, leveraging principles of bioinformatics. The course will cover essential steps of processing, analysis and interpretation of such data using commercial solutions for high performance computing (T-BioInfo) and open source applications (R).
This program is a collaborative effort between LBRN, BioMMED and Pine Biotech.
Program overview, goals and structure. Transcriptomics 1, part 1
Statistical tests, Differential Gene Expression. Transcriptomics 2, part 1
Correlation, Analysis of Variance and Factor Regression Analysis. Transcriptomics 2, part 2
Principles of data-driven thinking. Transcriptomics 3
Dimensionality Reduction. Transcriptomics 3
Differential Pathway enrichment. Transcriptomics 3
Working with files and tables in bash and R. PCA: biomedical data visualization in R