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a web application to apply/develop analysis tools for Molecular and Clinical data

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Oncoscape

Oncoscape is a web application that hosts an integrated suite of analysis tools for users to explore hypotheses related to molecular and clinical data in order to better understand cancer biology and treatment options.

--Intro and Demo and videos coming soon

See our website to start analyzing TCGA data using tools hosted by STTR at Fred Hutch or follow the Installation instructions to install and run Oncoscape on your own machine. Contribution from external developers is not only welcome, but encouraged; please see our contributing guidelines for details.

Version: oncoDev14 (Release)

Last Modified 8/20/15

Oncoscape is developed at the Fred Hutchinson Cancer Research Center under the auspices of the Solid Tumor Translational Research initiative.

Oncoscape is as an SPA -- a single page web application -- using JavaScript in the browser and R (primarily) on the backend server. It is an R package, though the immediate web-facing http server, currently written in R, will likely change over time to a more traditional architecture.

The goal of Oncoscape is to provide browser-based, user-friendly data exploration tools for rich clinical and molecular cancer data, supported by statistically powerful analysis. R is very well-suited to handling data, and performing analysis. JavaScript in the browser provides a rich and nimble user experience. Data & methods are sent and received through websockets using the chinook protocol (https://github.com/oncoscape/chinook) for message passing.

Oncoscape's design encourages custom deployments focused on any clinical/molecular data set. Oncoscape, here at GitHub, ships with patient and molecular data from the TCGA.

Main Components:

  • oncoDev14 - main oncoscape code with all tabs/submodules
  • dataPackages - clinical and molecular data files and API
  • analysisPackages - computational methods that execute on passed data
  • Optional:
    • Rlibs - local installation folder for running compiled packages

Install

Oncoscape can be installed within a local Rlibs folder or within the native R application. Read INSTALL.md for instructions.

Configure

Oncoscape requires several R dependencies, which can easily be obtained using Bioconductor's biocLite source repository. Data and analysis packages can be installed independently, but should reside in the same installation directory as Oncoscape. Note that the PatientHistory and SttrDataPackage are required base classes of the data packages.

Documentation

Documentation for each module and dataset can be found within the respective R package. An overview of how to contribute new modules is under development. For comments, questions or suggestions, please contact us through the outlets listed below.

Update

OncoDev14 (v1.4.60) was built and tested under R version >=3.2.1 The latest release of Oncoscape is maintained under the 'master' branch of our GitHub repository, while the beta version includes upcoming enhancements maintained under the 'develop' branch.

Authors

The code base for Oncoscape was written by Paul Shannon, Lisa McFerrin, Hamid Bolouri, and Jenny Zhang under the direction of the STTR at Fred Hutch.

Contact

To report any bugs, submit patches, or request new features, please log an issue in our issue tracker. For direct inquiries, please send an email to contact@oncoscape.org.

STTRcancer Fred Hutchinson Cancer Research Center 1100 Fairview Ave N Seattle, WA 98109

LICENSE

Copyright (c) 2014 Solid Tumor Translational Research http://www.sttrcancer.org

The MIT License (MIT)

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