Giter Club home page Giter Club logo

cancer-data's Introduction

Cancer data acquisition and processing for Project Cognoma

This is a mixed notebook and data repository for retrieving cancer data for Project Cognoma. Currently, all data is from the TCGA Pan-Cancer collection of the UCSC Xena Browser.

Workflow

The data acquisition and analysis is executing by running Jupyter notebooks in the following order:

The execute.sh script executes the notebooks in order. After installing and activating the environment, run with the command bash execute.sh from the repository's root directory.

Directories

The repository contains the following directories:

  • download — contains files retrieved from an external location whose content is unmodified. Large downloaded files are tracked using Git LFS. Associated metadata files are also retained for versioning.
  • data — contains generated datasets. The complete matrix files are not currently tracked due to file size, but randomly-subsetted versions are available for development use (see data/subset).

Download

DOI: 10.6084/m9.figshare.3487685

The complete datasets created by this repository (data/expression-matrix.tsv.bz2 and data/mutation-matrix.tsv.bz2) are uploaded to figshare. Since this is a manual process, check the figshare REFERENCES section to see which commit these datasets derive from. In other words, the latest version on figshare may lag behind this repository.

Environment

This repository uses conda to manage its environment, which is named cognoma-cancer-data. The required packages and versions are listed in environment.yml. If as a developer, you require an additional package, add it to environment.yml.

The following commands install and activate the environment:

# Create or overwrite the cognoma-cancer-data conda environment
conda env create --file=environment.yml

# Activate the conda environment (assumes conda >= 4.4)
conda activate cognoma-cancer-data

License

This repository is dual licensed as BSD 3-Clause and CC0 1.0, meaning any repository content can be used under either license. This licensing arrangement ensures source code is available under an OSI-approved License, while non-code content — such as figures, data, and documentation — is maximally reusable under a public domain dedication.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.