Welcome to PED Analytics, a feature for mining and analysing pancreatic-derived -omics data.

The data sources accessed by PED Analytics are datasets publicly-available in ArrayExpress, Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), Genomics Evidence Neoplasia Information Exchange (GENIE) and the Cancer Cell Line Encyclopedia (CCLE). PED Analytic provides you with the means to conduct exploratory and in-depth analyses of transcriptomic, sequencing, genomic and mutation data obtained from both tissues and cell lines.

PubMed: An automated data selection and retrieval system has been implemented. Publications of interest are identified from PubMed. Gene Expression Omnibus or ArrayExpress identifiers are used to establish computational links between the literature and any associated data. If data is available in the public domain, the system accesses the repository and downloads the relevant data files. These are fed into the relevant analytical pipelines and made available from the PubMed tab.

TCGA: The Cancer Genome Atlas is a consortium dedicated to the systematic study of alterations in a variety of human cancers. It has made publicly available mRNA expression, DNA copy number, mutation and methylation data, alongside its associated clinical data for a range of cancer types/subtypes. Currently, mRNA expression, DNA copy number and mutation data are available for analysis, with methylation data to follow shortly.

GENIE: Genomics Evidence Neoplasia Information Exchange is a pilot project that seeks to identify and validate genomic biomarkers relevant to cancer treatment by linking tumour genomic data from clinical sequencing efforts with longitudinal clinical outcomes. It has made publicly available DNA copy number and mutation data, alongside its associated clinical data for a range of cancer types/subtypes.

CCLE: Cancer Cell Line Encyclopedia project is an effort to conduct a detailed genetic characterization of a large panel of human cancer cell lines. mRNA expression, DNA copy number and mutation data for pancreatic cancer cell lines are available from this tab.

Once you have selected a source, you will be directed to a page from which you will be able to conduct multiple analyses: principal component analysis (PCA), estimates of tumour purity, gene expression plots, expression correlation and survival analyses, gene networks, copy-number alteration and integrative analyses, CIRCOS plots, as well as search for mutations and gene fusions.

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