Skip to content

CacconeLabYale/argot2-batch-data-prep

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Argot2 batch data prep

  • version number: 0.0.1
  • author: Gus Dunn

Overview

This pipeline prepares the blast/hmmer data files needed to run a batch session on Argot2 servers.

Details

TBA

Snakemake

This pipeline was constructed with the python-based Snakemake as its pipeline runner. Snakemake is very similar to Make but with a number of extra goodies including the ability to embed python logic right into the pipeline definition file.

This pipeline SHOULD be able to be run without intimate knowledge of how Snakemake works, but the user would do well to at least become familiar with how Snakemake and/or Make-like pipelines function. It will make debugging problems much more productive!

Installation

The best way to install this pipeline is to use conda which is part of the Anaconda distribution of Python. That will install all runtime dependencies including non-python packages needed to run this pipeline at once. And it will install them into a sequestered execution environment which protects your main system from the peculiarities of the versions of programs that may be needed to reproduce this pipeline's results. Conversely, it also protects this pipeline from most of the peculiarities of your system.

Installing Anaconda

Please follow the recommendations outlined in the conda documentation that best fits the system you are using.

Install with conda

First get the repo via git:

$ git clone https://github.com/xguse/argot2-batch-data-prep.git

Or via downloading a zip of the repository via the project's github page.

Next enter the pipeline directory that you just obtained and run the following commands (where ENV_NAME is a name you pick to refer to the conda environment that you will use to execute the pipeline):

$ conda create -n ENV_NAME --file requirements.txt

Basic usage

  1. Navigate to the pipeline directory.

  2. Switch to the correct conda execution environment.

    $ source activate ENV_NAME
  3. Run the pipeline via the snakemake command.

    $ snakemake --configfile path/to/your/configfile.yaml  -s main.snake all

Configuration files

Generally, you should be able to just copy a relevant config file from the configs directory in this pipeline's main directory.

This section should be used by the author to document particularities regarding the structure and meaning of the configuration file format and/or specific values.

Contributing

TBA

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 85.2%
  • Shell 8.6%
  • Rebol 6.2%