Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a power...

The Cancer Genome Atlas (TCGA) is supported by the National Cancer Institute and the National Human Genome Research Institute to chart the molecular landscape of tumor samples for more than 20 types of cancer [1-3]. TCGA has been generating multi-modal genomics, epigenomics, and proteomics data for thousands of cancer patients, providing unprecedented opportunities for researchers to systematic...

Data sharing is critical to advance genomic research by reducing the demand to collect new data by reusing and combining existing data and by promoting reproducible research. The Cancer Genome Atlas (TCGA) is a popular resource for individual-level genotype-phenotype cancer related data. The Database of Genotypes and Phenotypes (dbGaP) contains many datasets similar to those in TCGA. We have cr...

The cancer genome atlas project (TCGA) represents one of the largest sources of mRNA-seq data collected from human tumors. The expression profile of CD, receptor tyrosine kinase, and nuclear hormone receptor transcripts within this data set was investigated using a number of methods including DESeq and t-SNE based clustering. These gene families mediate cell-to-cell communication, adhesion, imm...

MOTIVATION Massive amounts of high-throughput genomics data profiled from tumor samples were made publicly available by the Cancer Genome Atlas (TCGA). RESULTS We have developed an open source software package, TCGA2STAT, to obtain the TCGA data, wrangle it, and pre-process it into a format ready for multivariate and integrated statistical analysis in the R environment. In a user-friendly for...

The Cancer Genome Atlas (TCGA) Research Network is an ambitious multi-institutional consortium effort aimed at characterizing sequence, copy number, gene (mRNA) expression, microRNA expression, and DNA methylation alterations in 30 cancer types. TCGA data have become an extraordinary resource for basic, translational, and clinical researchers and have the potential to shape cancer diagnostic an...

The Cancer Genome Atlas (TCGA) is a public funded project that aims to catalogue and discover major cancer-causing genomic alterations to create a comprehensive "atlas" of cancer genomic profiles. So far, TCGA researchers have analysed large cohorts of over 30 human tumours through large-scale genome sequencing and integrated multi-dimensional analyses. Studies of individual cancer types, as we...

Identification of novel prognostic biomarkers typically requires a large dataset which provides sufficient statistical power for discovery research. To this end, we took advantage of the high-throughput data from The Cancer Genome Atlas (TCGA) to identify a set of prognostic biomarkers in head and neck squamous cell carcinomas (HNSCC) including oropharyngeal squamous cell carcinoma (OPSCC) and ...

Gliomas, the most common primary brain tumor in humans, include a spectrum of disease. High-grade gliomas (HGG), such as glioblastoma, may arise from low-grade gliomas (LGG) that have a more indolent course. The process of malignant transformation (MT) of LGG to HGG is poorly understood but likely involves the activation of signaling programs that suppress apoptosis. We previously showed that S...