Metadata-Version: 2.1
Name: proMAD
Version: 0.3.2
Summary: Semiquantitative densitometric measurement of protein microarrays
Home-page: https://proMAD.dev
Author: Anna Jaeschke; Hagen Eckert
Author-email: 
License: MIT
Download-URL: https://github.com/theia-dev/proMAD/archive/v0.3.2.zip
Description: # proMAD <img src='https://github.com/theia-dev/proMAD/raw/master/proMAD/data/templates/logo.png' align="right"/>
        Semiquantitative densitometric measurement of protein microarrays
        
        
        [![PyPi](https://img.shields.io/pypi/v/proMAD.svg?style=for-the-badge)](https://pypi.org/project/proMAD/)
        [![Status](https://img.shields.io/pypi/status/proMAD.svg?style=for-the-badge)](https://pypi.org/project/proMAD/)
        [![License](https://img.shields.io/github/license/theia-dev/proMAD.svg?style=for-the-badge)](https://github.com/theia-dev/proMAD/blob/master/LICENSE.txt)
        
        [![Github issues](https://img.shields.io/github/issues/theia-dev/proMAD.svg?style=for-the-badge)](https://github.com/theia-dev/proMAD/issues)
        [![Coverage](https://img.shields.io/coveralls/github/theia-dev/proMAD?style=for-the-badge)](https://coveralls.io/github/theia-dev/proMAD)
        [![Build](https://img.shields.io/travis/theia-dev/proMAD.svg?style=for-the-badge)](https://travis-ci.org/theia-dev/proMAD)
        
        
        [![DOI](https://img.shields.io/badge/DOI-10.1186%2Fs12859--020--3402--4-green?style=for-the-badge)](https://doi.org/10.1186/s12859-020-3402-4)
        [![Documentation](https://img.shields.io/readthedocs/promad.svg?style=for-the-badge)](https://promad.readthedocs.io)
        
        
        
        ## Setup
            pip install proMAD
            
        You can also install the latest version directly from GitHub.
        
            pip install -U git+https://github.com/theia-dev/proMAD.git#egg=proMAD
        
            
        ## Usage
        **ArrayAnalyse**
        ```python
        from proMAD import ArrayAnalyse
        aa = ArrayAnalyse('ARY022B')  # set array type
        aa.load_collection('tests/cases/prepared', rotation=90)  # set input folder
        
        aa.evaluate("A6")  # get result dictionary
        aa.get_spot("A6")  # get underlying image data
        aa.evaluate()  # get result dictionary for all spots
        
        aa.report('report.xlsx')  # export the results
        ```
        **Cutter**
        
        * interactive
        ```python
        from proMAD import Cutter
        c = Cutter()
        
        c.load_collection('tests/cases/raw')  # set input folder
        c.set_shape()  # ask for the shape
        c.guess_positions()  # use a simple guess as a starting point
        c.preview()  # display guess (uses the last loaded image as default)
        
        c.set_positions()  # ask for refined cut positions
        c.set_names()  # ask for names
        c.preview()  # check in the preview
        c.save_images('test/cases/formatted_image_folder')  # save to folder (will be created if it does not exist)
        ```
        
        * direct
        ```python
        from proMAD import Cutter
        
        c = Cutter()
        
        c.load_collection('tests/cases/raw')  # set input folder
        c.shape = (2, 3)
        c.cut_positions = [[20, 225, 445], [40, 130, 217, 315]]
        c.names = [['OL', 'ML', 'UL'], [None, 'MR', 'UR']]
        c.preview()
        c.save_images('test/cases/formatted_image_folder')  # save to folder (will be created if it does not exist)
        ```
        
        ## Citation
        If you use proMAD in your work please cite the following [article](https://doi.org/10.1186/s12859-020-3402-4).
        
        
        > Jaeschke, A., Eckert, H. & Bray, L.J.
        > proMAD: semiquantitative densitometric measurement of protein microarrays. 
        > *BMC Bioinformatics* **21**, 72 (2020). 
        > doi: [10.1186/s12859-020-3402-4](https://doi.org/10.1186/s12859-020-3402-4)
        
        ***
        
        The full source code can be accessed on [GitHub](https://github.com/theia-dev/proMAD) with the corresponding documentation hosted at [Read the docs](https://promad.readthedocs.io).
        
Keywords: protein,microarrays,densitometric
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: ~=3.6
Description-Content-Type: text/markdown
