Pre-Processed Cancer Multi-Omic Data from TCGA and Synthetic Data

<p><strong>ABSTRACT&nbsp;</strong></p> <p>It contains the data of four omic profiles (CNV, mRNA, miRNA, and protein) obtained for BRCA, LGG, and LUAD obtained from the TCGA project.&nbsp;</p> <p>In addition, we provide synthetic data for a mixture of isotropic distributions.</p> <p><strong>Instructions:&nbsp;</strong></p> <p>Cancer data are identified by cancer type (LGG: low-grade glioma, BRCA: breast cancer, and LUAD: lung cancer). The data are scaled by using the minima and maxima of each column so that the values are between 0 and 1. In these files, the columns are the features and the rows correspond to the patients.</p> <p>The summary data contains only the numerical values. The columns are the features and the rows are the observations.</p> <p><strong>Inspiration:</strong></p> <p>This dataset uploaded to U-BRITE for &quot;AI against CANCER DATA SCIENCE HACKATHON&quot;</p> <p>https://cancer.ubrite.org/hackathon-2021/</p> <p><strong>Acknowledgements</strong></p> <p>Diego Salazar, June 20, 2021, &quot;Pre-processed Cancer multi-omic data from TCGA and synthetic data&quot;, IEEE Dataport, doi: https://dx.doi.org/10.21227/pjb8-d090.</p> <p>https://ieee-dataport.org/documents/pre-processed-cancer-multi-omic-data-tcga-and-synthetic-data</p> <p><strong>U-BRITE last update date:</strong>&nbsp;07/21/2021</p>