English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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 comprehensive tool that provides a complete integrative analysis harnessing 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 downstream 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 and by using Roadmap and ENCODE data, we provide a workplan to identify candidate 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). This workflow introduces the following Bioconductor packages:  AnnotationHub ,  ChIPSeeker ,  ComplexHeatmap ,  pathview ,  ELMER ,  GAIA ,  MINET ,  RTCGAtoolbox ,  TCGAbiolinks .

TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages