This course is now full with a waiting list.
Experiments designed to quantify gene expression often yield hundreds of genes that show statistically significant differences between two classes (two biological states, two phenotype states, two experimental conditions, etc). Once differentially expressed genes are identified, enrichment analysis (EA) methods can be conducted to identify groups of genes (e.g. particular pathways) that are differentially expressed, and offer insights into biological mechanisms. One example of such a method is the Gene Set Enrichment Analysis (GSEA), which is very popular and frequently used for high-throughput gene expression data analysis.
This course will cover GSEA and alternative enrichment tools. Since most of their implementations are directly linked to databases that annotate the function of genes in the cell, the course will also introduce GO enrichment analysis.
Biologists eager to identify a statistically reliable set of genes that are differentially expressed.
At the end of the course, the participants will be able to:
Knowledge / Competencies
Registration fees are 60 CHF for academics and 300 CHF for for-profit companies.
Deadline for free-of-charge cancellation is set to 11/06/2021. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to our general conditions.
This course will be streamed.
The course will start at 9:00 and end around 17:00. Precise information will be provided to the participants on due time.
Coordination: Valeria Di Cola, SIB training group.
We will recommend 0.25 ECTS credits for this course (given a passed exam at the end of the course).
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