Academic Medical Center (AMC)
Department of Oncogenomics, M1-132, Meibergdreef 9, 1105 AZ Amsterdam
+31 20 56 67536
In this era of explosive high throughput (HT) data in molecular biology, there is a growing need for accessible software solutions that can help unlock biological/clinical characteristics from such data.
Given the complexity, high throughput data such as RNAseq, are often analyzed by (bio-) informaticians, and not the biologist / biomedical researcher that performed the experiment. With the biomedical researcher (with limited or no bioinformatics skills) in mind as the end-user, the bioinformatics sub-team of the department of Oncogenomics, AMC (header by Dr. Jan Koster) developed the R2 platform (http://r2.amc.nl), enabling them to work with their own data from anywhere at any time.
The R2 platform is a freely accessible online genomics analysis and visualization tool which can analyze a large collection of public data, but also allows shielded analysis of private dataset(s). R2 consists of a database, storing the genomic information, coupled to an extensive set of tools to analyze/visualize the datasets. Analyses within the software are highly connected, allowing quick navigation between various aspects of the data mining process. In addition, results from an initial analysis can be investigated further from within the platform. Since R2 contains an extensive body of publicly available sample collections, this enables users to also relate their findings to other diseases and or tissues in integrative analyses.
Because the R2 bioinformatics team is embedded in a large molecular biology research group, development of the platform was guided by requirements of molecular biologists, thereby contributing to its user friendliness.
In the public section, R2 hosts a large collection of HT samples, and is constantly extended. Next to gene expression (microarrays and RNA-Seq), the platform is also being employed for the integration, analysis and visualization of other data types, such as aCGH, SNP, ChIP, methylation, miRNA, IC50, ChIP-seq, and NGS exome or whole genome sequencing information (some on a collaborative basis). When data has been made accessible to the web-platform a wealth of analyses can be performed quickly (most results are available in less than a minute). As such R2 provides a central starting point from where a range of data mining and analysis paths can be followed within one environment.
R2 contains an expanding set of interactive analyses which are heavily inter-connected, allowing users to quickly hop from one view (representation of the data) to another. Analyses include correlation, differential expression, gene sets, gene ontology, transcription factor binding sites, tSNE, PCA, k-means, Kaplan Meier survival scans, signature creation etc. Visualizations include various gene oriented plots, heatmaps, Circos plots, embedded genome browser, Venn diagrams, etc. The real power of the platform lies in the chaining of results of analyses; e.g. the results of a differential expression analysis can be further trimmed down using a Kaplan Meier analysis that in turn can be used for a Gene Ontology over-representation analysis. Furthermore, the webserver allows for overviews across different datasets (such as MegaSampler and 2D distribution).
R2 allows for the shielding of data that has not been published yet. While in the process of analyzing the clinical or experimental data, the analyses can be shared with other R2 users of choice via our community options. This makes R2 an outstanding environment for scientific collaboration.
The R2 analysis tools have thus far been used in more than 800 peer-reviewed scientific publications including journals as Nature and Cell. The webservers have been serving over 1.600.000 pages over the past 12 months (Sept 2018). Many parts of the R2 platform (http://r2.amc.nl) are publicly accessible and intended to be used by biologists, even those with little or no bioinformatics training.
- Biomedical & health
Expertise and Track Record
We have extensive experience in making the analysis and visualization of various types of omics data accessible to biomedical researchers, thereby allowing them to test their hypothesis. We are constantly adapting the platform with options requested by our users.
We have participated in more than 120 peer-reviewed scientific publications, related to the R2 platform. The platform itself has been cited in many more. Please see the up to date CV of R2 here.