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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Create a visual Fisher's Exact plot in a few simple clicks in the R2 Genomics Analysis & Visualization platform

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Create a visual Fisher's Exact plot in a few simple clicks in the R2 Genomics Analysis & Visualization platform ( https://r2.amc.nl ). Just see the whole process in action in the illustration below. The Fisher's Exact test is often used to demonstrate whether the proportions of 2 different categorical variables are equal to the expectation. A significant p-value then informs you that this is unlikely (when used as a 2-sided test). Within R2, we add a visual element to such a test, where you can see the different groups in the contingency table as separate dots. These dots, are linked to actual samples in the data set, and can thus also be decorated using their meta data (color by a grouping variable), or even by the expression of any gene. As such you can add another layer in your interpretation. Just have a look at the animation above on how you can easily use this powerful option within the R2platform. The R2 open access online data science platform, designed for biomedic...
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TCGA Barcodes (Sample Types)

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The Cancer Genome Atlas Program (TCGA) is one of the cornerstones of cancer research. Every sample has a unique identifier, also known as barcode. A basic understanding of the naming convention is very helpful to quickly assess the 'type of sample' that you are working with. The sample type is contained in the numerical part of the 4th element of a barcode, that can be up to 7 parts. Barcodes most commonly are composed of 4 parts, which is informative for most use cases. Code Definition 1 Primary Solid Tumor 2 Recurrent Solid Tumor 3 Primary Blood Derived Cancer - Peripheral Blood 4 Recurrent Blood Derived Cancer - Bone Marrow 5 Additional - New Primary 6 Metastatic 7 Additional Metastatic 8 Human Tumor Original Cells 9 Primary Blood Derived Cancer - Bone Marrow 10 Blood Derived Normal 11 Solid Tissue Normal 12 Buccal Cell Normal 13 EBV Immortalized Normal 14 Bone Marrow Normal 15 sample type 15 16 sample type 16 20 Control Analyte 40 Recur...
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