https://github.com/greenelab/cimr

tool for continuously integrated meta-resource
https://github.com/greenelab/cimr

continuous-integration gene-expression gtex gwas twas

Last synced: about 1 month ago
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tool for continuously integrated meta-resource

• Host: GitHub
• URL: https://github.com/greenelab/cimr
• Owner: greenelab
• License: other
• Created: 2018-09-04T17:34:27.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-03-25T22:46:31.000Z (almost 4 years ago)
• Last Synced: 2024-11-01T10:16:10.365Z (about 2 months ago)
• Topics: continuous-integration, gene-expression, gtex, gwas, twas
• Language: Python
• Homepage: https://cimr.readthedocs.io/
• Size: 34.3 MB
• Stars: 1
• Watchers: 5
• Forks: 2
• Open Issues: 3
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE.md

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README

        


****

cimr

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cimr is not yet released for public use

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=====================================================

continuous integration and analysis of complex traits

=====================================================

==========

YoSon Park

==========

**Useful links**:

`Source repository `_ |

`Issues & Ideas `_ |

`Documentation `_ |

`cimr-d `_

*cimr* (continuously integrated meta-resource) is a convenience tool

for continuous analyses of variant-based association results from

GWAS (genome-wide association studies), eQTL (expression-quantitative

trait loci mapping) or other association studies. cimr aims to

streamline the pre-analysis processing steps, provide standardized

input files and automate scripting for standard downstream analyses.

============

Installation

============

-----------------

Installing python

-----------------

cimr requires python :math: `\ge` 3.6. Installation of data analysis bundles

such as `miniconda `_ or

`anaconda `_ are recommended and will

install all python packages cimr depends on. However, all required python

packages can be downloaded and installed with setup.py or requirements.txt

provided here.

------------------

Installing git lfs

------------------

cimr-d and some functionalities in cimr may use

`git large file storage (LFS) `_ .

See how to install

`git `_ .

To install git-lfs on Ubuntu, run::

    curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash

    sudo apt-get install -y git git-lfs

    git-lfs install

Alternatively, you can install git-lfs through conda::

    conda install -c conda-forge git-lfs && git lfs install

---------------

Installing cimr

---------------

You can use pip to install the latest stable release of cimr::

    pip3 install cimr

If you want to try out the nightly build of cimr at your own risk,

clone the repository from git::

    git clone https://github.com/greenelab/cimr.git

    cd cimr

    pip3 install -r requirements.txt

    python3 setup.py build

    python3 setup.py install

=================

Analysis examples

=================

------------------------------------------------------------------------

Quality assurance and processing of association summary statistics files

------------------------------------------------------------------------

You can use cimr to standardize public datasets using a yaml file, e.g.::

    # example.yaml

    data_file:

        description: >-

            Global Lipid Genetics Consortium GWAS results for high-density

            cholesterol levels

        location:

            url: https://zenodo.org/record/3338180/files/HDL_Cholesterol.txt.gz

            md5: 2b28816a0a363db1a09ad9a6ba1a6620

        columns:

            variant_id: panel_variant_id

            variant_chrom: chromosome

            variant_pos: position

            rsnum: variant_id

    data_info:

        citation: 10.1038/ng.2797

        data_source: http://lipidgenetics.org/

        data_type: gwas

        context: hdl cholesterol

        build: b38

        sample_size: 187167

        n_cases: na

        can_be_public: true

    method:

        name: linear regression

        tool: PLINK;SNPTEST;EMMAX;Merlin;GENABEL;MMAP

        website: >-

            http://zzz.bwh.harvard.edu/plink/download.shtml;

            https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html;

            https://genome.sph.umich.edu/wiki/EMMAX;

            https://csg.sph.umich.edu/abecasis/Merlin/tour/assoc.html;

            http://www.genabel.org/sites/default/files/html_for_import/GenABEL_tutorial_html/GenABEL-tutorial.html;

            https://mmap.github.io/

    contributor:

        name: Contributor Name

        github: contributorgithub

        email: [email protected]

Details can be found in the

`cimr-d contributions.md `_.

Once the yaml file is prepared, you can run cimr locally::

    cimr processor -process -yaml-file example.yaml