The Human Epigenome Browser at Washington University
By Xin Zhou, Brett B. Maricque, Mingchao Xie, Daofeng Li, Vasavi Sundaram, E. A. Martin, Brian C. Koebbe, C. Nielsen, M. Hirst, P. Farnham and 8 more. Nature Methods, 2011
315 citations recorded by the source corpus.
To the Editor: Advances in next-generation sequencing have reshaped the landscape of genomic and epigenomic research. Large consortia such as the Encyclopedia of DNA Elements, the Roadmap Epigenomics Mapping Consortium and The Cancer Genome Atlas have generated tens of thousands of sequencingbased genome-wide datasets, creating a reference and resource for the scientific community. Small groups of researchers now can rapidly obtain huge volumes of genomic data, which need to be placed in the context of the consortium data for comparison. These data are often accompanied by rich metadata describing the sample and experiment, which is critical for their interpretation. Visualizing, navigating and interpreting such data in a meaningful way is a daunting challenge1. We developed the Human Epigenome Browser to host Human Epigenome Atlas data produced by the Roadmap Epigenomics Project2 and to support navigation of the Atlas and its interactive visualization, integration, comparison and analysis (http://epigenomegateway.wustl.edu/; see Supplementary Note and Supplementary Protocol for main components and use). The Browser is web-based, and it extends the seminal concept introduced by the University of California Santa Cruz Cancer Genomics Browser3 to support large, sequencing-based datasets. Epigenome measurements are displayed as genome heatmaps in which color gradients reflect signal strength (Fig. 1 and Supplementary Fig. 1). Metadata such as cell type, assay type, epigenetic mark and phenotype of the sample are encoded numerically and displayed in different colors by a metadata heatmap next to the genome heatmap (Fig. 1 and Supplementary Figs. 2–4). Investigators can zoom and pan in a ‘Google Maps’–like style to examine dozens to
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/753e68ad24f6555d4cd2067f4f3d12e7c14f164b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- C. Hui
- Christoph Bock
- D. J. Drucker
- Manolis Kellis
- Nezar Abdennur
- Jason Ernst
- Lucas D. Ward
- Chaopeng Shen
Citations in the corpus
- Analysing and interpreting DNA methylation data (2012, methodology): “The resulting files are uploaded to a Web‑accessible directory and imported into a Web‑based genome browser for visualization (for exam‑ ple, UCSC Genome Browser 70 , Ensembl 71 or WashU Human Epigenome Browser 72 ).”
- hTFtarget: A Comprehensive Database for Regulations of Human Transcription Factors and Their Targets (2019, unknown): “hTFtarget was implemented with HTML, JavaScript (https://www.javascript.com/), Python (https://www.python.org/), Flask (http://flask.pocoo.org/), Bootstrap (https://getbootstrap.com/), AngularJS (a model-view-controller frame for Javascript web service, https://angularjs.org), and WashU EpiGenome Br”
- FTO Obesity Variant Circuitry and Adipocyte Browning in Humans (2015, methodology): “edu/roadmap/ and can be visualized in the WashU Epigenome Browser.(3) We used annotations of chromatin states(2) based on combinations of histone modification marks, using a 25-state model predicted by ChromHMM(4), using 12 histone modification marks imputed by ChromImpute(5).”