Metadata-Version: 2.1
Name: doepipeline
Version: 1.1.0
Summary: Package for optimizing pipelines using DoE.
Home-page: https://github.com/clicumu/doepipeline
Author: Rickard Sjogren
Author-email: rickard.sjogren@umu.se
License: MIT
Description: # doepipeline
        
        This is yet another pipeline package. What distinguishes `doepipeline` is
        that it enables pipeline optimization using methodologies from statistical
        [Design of Experiments (DOE)](https://en.wikipedia.org/wiki/Design_of_experiments).
        
        # Features
        * Community developed: Users are welcome to contribute to add additional funtionality.  .
        * Installation: Easy installation through [conda](http://conda-forge.org/) or [PyPI](https://pypi.org/).
        * Generic: The optimization is useful for all kinds of CLI applications.
        
        
        # Quick start links
        Take a look at the [wiki documentation](https://github.com/clicumu/doepipeline/wiki) to getting started using doepipeline. Briefly, the following steps are needed to start using doepipeline.
        
        1. [Install doepipeline](https://github.com/clicumu/doepipeline/wiki/Installation)
        2. [Create configuration file](https://github.com/clicumu/doepipeline/wiki/Configuration-file)
        3. [Run optimization](https://github.com/clicumu/doepipeline/wiki/Usage)
        
        Four example cases (including data and configuration) are provided to as help getting started; 
        1) [de-novo genome assembly](https://github.com/clicumu/doepipeline/wiki/Case-1)
        2) [scaffolding of a fragmented genome assembly](https://github.com/clicumu/doepipeline/wiki/Case-2)
        3) [k-mer taxonomic classification of ONT MinION reads](https://github.com/clicumu/doepipeline/wiki/Case-3) 
        4) [genetic variant calling](https://github.com/clicumu/doepipeline/wiki/Case-4)
        
        
        # Cite
        __doepipeline: a systematic approach for optimizing multi-level and multi-step data processing workflows__ Svensson D, Sjögren R, Sundell D, Sjödin A, Trygg J BioRxiv doi: https://doi.org/10.1101/504050
        
        # About this software
        doepipeline is implemented as a Python package. It is open source software made available
        under the [MIT license](LICENSE).
        
        If you experience any difficulties with this software, or you have suggestions, or want
        to contribute directly, you have the following options:
        
        - submit a bug report or feature request to the 
          [issue tracker](https://github.com/clicumu/doepipeline/issues)
        - contribute directly to the source code through the 
          [github](https://github.com/clicumu/doepipeline) repository. 'Pull requests' are
          especially welcome.
        
Keywords: pipeline doe optimization
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
