
From presentation to your own analysis¶
Overview¶
The presentations provide a quick glance over most functionalities of R2. Many of these functionalities are described in the Online Tutorial (r2platform.com/tutorial) as well.
You might wonder how to do the shown analyses yourself. The links below connect the topics of the presentation directly to the respective chapters in the tutorial where step by step instructions guide you through an analysis, which you can perform online within R2 yourself.
During these steps features related to the respective topic will be introduced, such as additional analyses or visualizations, thereby conveying the ease of using the interconnected R2 interface.
You choose which modules you find interesting and try them out following the step-by-step guides on the R2 platform. Above all, we encourage you to tweak the guides to your interest: find datasets that are closely related to your research topic and play around with the modules; fill in settings (genes, gene sets, chromosome locations etc) that are aligned with your research questions.
Our platform interface undergoes frequent improvements. It might be that you come across small interface discrepancies. Most of the time, you will find the relocation of the button or name change of the functionality. If not, please ask us for help or email us at r2-support@amsterdamumc.nl.
You can find an overview of the chapters per presentation topic below:
First presentation¶
Basics of R2:
Graphics settings/ Track visibility
Differential Expression:
Differential expression between two / multiple groups
Genes correlating with your gene of interest /Gene Ontology analysis / Gene set analysis
Storing of the result as personal gene set / Finding your custom and saved genesets
Correlations with a gene:
Second presentation¶
Cohort subgroups:
Signature Scores /Geneset vs Geneset correlation
More than 1 dataset:
Genome Browser:
Datascopes
Adapting R2
More advanced topics¶
The following are not part of the Basics workshops, but they could be interesting topics for some researchers
Integrative Analysis
Somatic mutation data: WGS/NGS