R2platform Data Science Annals

  Ploting updates for the R2platform We have been working hard to bring you the latest update in the R2 genomics analysis and visualization platform ( https://r2.amc.nl ); the goto web-tool for biomedical researchers to test their hypotheses on public omics data, without the need for bioinformatics or coding expertise. In the latest update, we have made substantial changes to many of the plots that can be produced within R2. Many of the adaptable parameters have now become interactive and are placed under the 'gears' icon. The 'gears' icon Let's have a look at a gene within one of the many resources that are publicly available in R2. We will look at the GATA3 gene in an integrated resouce where samples from both GTEx as well as the TCGA have been integrated and 'batch corrected' to get an immersive view of expression in normal as well as cancer samples. We first select our resource of interest by clicking on 'select a data set'. and then find the ...

The R2 platform has been celebrating quite some achievements that we have never even considered when we started developeing the R2 platform. Some weeks ago, we reported on 2.500 citations for the R2 platform in NCBI PubMed. This was already a dream come through. Now we can report on yet another milestone. We have been visited by 250.000 unique IP addresses in the R2 platform. A major achievement that would not have been possible without the many users that serve as true ambassadors by spreading the word on the usefulness of the platform, especially for scientists that are not able to easily download, pre-process and subsequently analyse genomics data. And why should they, is they can also just visit R2 and click your way through a wide array of analytical options.   So spend your time thinking about the results, in stead of preparing the data.

  Quite frequently, you may want to provide a quick and easy to grasp plot that shows the expression of a couple of genes, segregated over a few groups. With single cell mRNA data, this also needs to take into account the fact that a gene if frequently not detected in all of the cells. Enter the bubble plot. This visualization will show the data much like a heatmap, where every sub-group is represented by a proportional circle. The dcolor here then reflects the average intensity value, while the circle size denotes a percentage of the cells that show expression. Within R2, we have also got this type of viaualization implemented, making it easy to use such insightful graphs with ease. How the circles are scaled can also be defined in different ways. You can look at this from the perspective of the total data set size, and represent the data as a percentage of all the cells. Alternatively, you can also represent the data as a percentage of the cells represented within a group. This l...

 The R2 platform team tries its best to reach a diverse scientific audience via an array of channels. For one, we maintain this blog, with occasional stories and notifications on what keeps us busy ;) We also use social media applaications such as X (formerly known as Twitter), Facebook, Instagram, Threads, LinkedIn, where we keep our users and others interested up to date on new developments and the latest data sets.  Another channel by which we provide tutorials and documentation is via the readthedocs sites, where we maintain our storytelling manual that spans more than 260 pages. However all of these are text based, which is great in many cases, but does requires persistence from the reader. So in order to reach even more users, we have also created a YouTube channel ( https://www.youtube.com/@R2GenomicsPlatform/ ). On this channel, we provide video demonstrations of common functions within the R2 platform, where we take you through every step to obtain a result. There are...

 When you are performing a differential expression analysis or any other search that can yield many potentially intersting genes, then one often performs a gene ontology search or a gene set enrichment analysis, to identify processes that may be at the root of the result set that was identified. At some point, you may also become interested in a single gene and want to know more about this. This is where the pubsniffer tool, that is embedded in the R2 plaftorm comes in handy.  Pubsniffer is an automated analysis that can identify how many papers are found around a particular gene. It also allows you to immediately launch a pubreminer session that will try to present you with a term frequency analysis, to quickly condense a vast amount of scientific literature into a clickable overview. When used with 2 genes, then pubsniffer will also report sentences from abstracts, where both genes are being mentioned, in an attempt to proide you with concise information to help you identify...

Also 2023, has been quite a successful year for the R2 platform up to now. Citations keep coming in, which are a clear sign to us, that we are still filling a space in the scientific domain, by allowing every researcher to do datamining and datascience analyses and visualizations, without the need for bioinformatics or coding ecpertise.   If there are analyses, ideas or other suggestions on how we could improve the R2 platform, then do not hesitate to let us know via the support address on the R2 website (https://r2.amc.nl) Some recent ctations included in the graph above: 2451 Julson JR  et.al.  (2023). CDK4/6 Inhibition With Lerociclib is a Potential Therapeutic Strategy for the Treatment of Pediatric Sarcomas.  J Pediatr Surg   :. 2450 Chen PD  et.al.  (2023). Decreased B4GALT1 promotes hepatocellular carcinoma cell invasiveness by regulating the laminin-integrin pathway.  Oncogenesis   12 :49. 2449 Ali W  et.al.  (2023). Surviva...