Enrichment analysis: interpret gene lists like a pro

Enrichment analysis: interpret gene lists like a pro

Gene enrichment analysis is the most popular systematic approach to assign ontologies, pathways, and transcription factors to gene lists usually resulted from high throughput experiments. This short course introduces the two most frequently applied methods to locate the common features of large gene lists, and provide opportunities to practice this analysis in the most common research scenarios using GeneTrail (for gene set enrichment analysis) and WebGestalt (for over-representation analysis), the two web tools used most often in the field.

You get written material, video explanations for the background, and prepared example data files for practices. You are provided with (almost) real life discussions between a wet-lab biologist and a bioinformatician to clarify the most common misunderstandings related to this analysis. You are led step by step by two experts of the field, both active researchers; and in the meantime, you are challenged to proof your knowledge in quizzes.

If you have a solid background in molecular biology research, you will be able to expert these methods in a maximum of 8-10 active course hours, but if you have only a general idea of the field, you will get a plenty of background material to learn and practice all in a few days. We recommend to cover all the provided material approximately in a week to maximize the efficiency of your learning.

As you know, bionformatics and data analysis skills are highly demanded among molecular biology and pharma researchers. Why not equip yourself with these easy but very useful tools to extend your future potential as a researcher?

How to get more information from the results of high throughput gene expression data with easy-to-use web tools?

Url: View Details

What you will learn

• You will learn how to perform over-representation and gene set enrichment analysis on microarray and RNA-Seq
• You will understand the relevant statistical approaches which are needed to find Gene Ontology, KEGG or other pathway terms which are associated with gene lists
• You will be able to design and execute such analysis

Rating: 3.9

Level: Intermediate Level

Duration: 43 mins

Instructor: Csaba Ortutay