Welcome to the R2platform DataScience Annals in 2023

Welcome to the R2platform DataScience Annals. This blog will serve as a low-level entry point to provide some insights into datascience that may also be applicable for users of the http://r2platform.com .

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R2: An Interactive Online Portal for Tumor Subgroup Gene Expression and Survival Analyses, Intended for Biomedical Researchers

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  R2: An Interactive Online Portal for Tumor Subgroup Gene Expression and Survival Analyses, Intended for Biomedical Researchers Genomic data from The Cancer Genome Atlas (TCGA) project has enabled comprehensive molecular profiling of diverse cancer types. The extensive sample size within TCGA provides an invaluable resource for investigating tumor heterogeneity. Effective exploration of this dataset by researchers and clinicians is essential for discovering novel therapeutic and diagnostic biomarkers. While numerous computational tools have been developed to analyze specific aspects of TCGA data, there remains a need for platforms that facilitate the study of gene expression variability and its association with clinical outcomes across tumors. Here, we introduce the  R2 Platform , an intuitive and interactive web portal designed for in-depth analysis of TCGA gene expression data. The portal leverages TCGA Level 3 RNA-seq and clinical data from 31 cancer types. With its user-f...
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Plot update for the R2platform

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  Plot update 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 'TC...
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Bubble plots

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  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...
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