Metadata-Version: 2.1
Name: correlationPlus
Version: 0.1.3
Summary:  Python package to plot and analyze dynamical correlations maps of proteins.
Home-page: https://github.com/tekpinar/correlationPlus
Author: Mustafa Tekpinar
Author-email: tekpinar@buffalo.edu
License: LGPL
Download-URL: https://github.com/tekpinar/correlationPlus
Description: # CorrelationPlus
        
        A Python API to plot and analyze dynamical correlations of proteins.
        
        CorrelationPlus contains three scripts that you can use to plot and analyze 
        dynamical correlations for proteins and biological macromolecules. 
        These correlations can be dynamical cross-correlations or linear mutual
        information. 
        
        mapAnalysis app plots and produces analysis scripts for 
        correlation maps. It can be more useful if your structure contains multiple
        chains. The program will produce an output for overall structure 
        and all individual intra-chain correlations, if exist. Moreover, the program 
        will give you inter-chain correlations, if you have more than one chain. 
        The program only requires a pdb file and a correlation data matrix. 
        The correlation data has to be in matrix format, where only A(i,j) values are 
        listed in a square matrix format. You can analyze the correlations with VMD 
        just by loading the tcl files produced by mapAnalysis module. 
        
        ## A Quick Start with correlationPlus Scripts
        
        To run a simple example, go to examples folder and then run:
        
        ```bash
        correlationPlus mapAnalysis -i 6fl9_just_prot_anm_100_modes_rc_15_cross-correlations.txt -p 6fl9_centeredOrientedAligned2Z.pdb -t absndcc
        ```
        This will produce plots of absolute values of dynamical cross correlations.
        
        Sometimes, we may need to plot difference map of two correlation maps. 
        For example, you may want to see the differences of linear mutual information 
        maps of produced with two different methods, conditions etc.
        This can be produced with diffMap app as follows:  
        
        ```bash
        correlationPlus diffMap -i 6fl9_rc15_scalCoeff1_100_modes_lmi_v2.dat -j zacharias_rc15_scalCoeff15_100_modes_lmi.dat -p 6fl9_centeredOrientedAligned2Z.pdb -t lmi
        ```
        
        Finally, correlationPlus can do centrality analysis for your protein
        via its centralityAnalysis app.
        
        It computes degree, closeness, betweenness, current flow closeness, 
        current flow betweenness and eigenvector centrality.
        
        ```bash
        correlationPlus centralityAnalysis -i 6fl9_just_prot_anm_100_modes_rc_15_cross-correlations.txt -p 6fl9_centeredOrientedAligned2Z.pdb -t absndcc
        ```
        
        ## Ipython Interface
        For a detailed analysis, script interfaces provided by mapAnalysis, diffMap and 
        centralityAnalysis apps may not be sufficient. Therefore, you can use IPython 
        to load the functions and do a detailed analysis as follows. 
        
        ```
        from correlationPlus.mapAnalysis import *
        ```
         
        
        You can get help for individual functions with
        
        ```
        help(intraChainCorrelationMaps) 
        
        ```
        You can check different valueFilters, distanceFilters for your analysis. 
        Even you can scan a range of values by calling the functions in a 
        loop. 
        
        
        ## Installation
        
        ### for users
        
        We recommend to use pip
        ```bash
        pip install correlationPlus
        ```
        
        or if you do not have administration rights
        ```bash
        pip install --user correlationPlus
        ```
        
        If you prefer to use a virtualenv
        ```bash
        python3.8 -m venv correlationPlus
        cd correlationPlus
        source bin/activate
        pip install correlationPlus
        ```
        
        ### for developers
        
        We recommend to use pip and a virtualenv
        ```bash
        python3.8 -m venv correlationPlus
        cd correlationPlus
        source bin/activate
        mkdir src
        cd src
        git clone https://github.com/tekpinar/correlationPlus.git # or git@github.com:tekpinar/correlationPlus.git
        cd correlationPlus
        pip install -e .
        ```
        
        ## Licensing
        
        correplationPlus is developed and released under GNU Lesser GPL Licence. 
        Please read to the COPYING and COPYING.LESSER files to know more. 
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.6
Description-Content-Type: text/markdown
