TCGAWorkflow            Biotechnological advances in sequencing have
                        led to an explosion of publicly available data
                        via large international consortia such as The
                        Cancer Genome Atlas (TCGA), The Encyclopedia of
                        DNA Elements (ENCODE), and The NIH Roadmap
                        Epigenomics Mapping Consortium (Roadmap). These
                        projects have provided unprecedented
                        opportunities to interrogate the epigenome of
                        cultured cancer cell lines as well as normal
                        and tumor tissues with high genomic resolution.
                        The Bioconductor project offers more than 1,000
                        open-source software and statistical packages
                        to analyze high-throughput genomic data.
                        However, most packages are designed for
                        specific data types (e.g. expression,
                        epigenetics, genomics) and there is no one
                        comprehensive tool that provides a complete
                        integrative analysis of the resources and data
                        provided by all three public projects. A need
                        to create an integration of these different
                        analyses was recently proposed. In this
                        workflow, we provide a series of biologically
                        focused integrative analyses of different
                        molecular data. We describe how to download,
                        process and prepare TCGA data and by harnessing
                        several key Bioconductor packages, we describe
                        how to extract biologically meaningful genomic
                        and epigenomic data. Using Roadmap and ENCODE
                        data, we provide a work plan to identify
                        biologically relevant functional epigenomic
                        elements associated with cancer.  To illustrate
                        our workflow, we analyzed two types of brain
                        tumors: low-grade glioma (LGG) versus
                        high-grade glioma (glioblastoma multiform or
                        GBM).
