Metadata-Version: 2.0
Name: olsapy
Version: 1.0.1
Summary: a package for orthogonal linear separation analysis (OLSA)
Home-page: https://github.com/tadahaya222/OLSApy
Author: tadahaya mizuno
Author-email: tadahaya@gmail.com
License: The MIT License (MIT)
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: pandas

Copyright (c) 2018 Tadahaya Mizuno

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Description-Content-Type: UNKNOWN
Description: ========
        OLSAPY
        ========
        
        OLSAPY: Orthogonal Linear Separation Analysis in Python
        =======================================================
        * OLSA is an analysis method of omics data to decompose the complex effects of a perturbagen into basic components.
        * OLSAPY is a package for OLSA in python.
        * OLSA can be applied to any kinds of omics data such as RNA-seq, proteome, and so on.
        
        Dependency
        =======================================================
        * python 3.6
        * requirements: numpy, pandas, scipy
        
        Setup
        =======================================================
        ::
        
         pip install olsapy
        
        Usage
        =======================================================
        1. prepare a profile matrix with variables in rows and samples in columns as a csv file
        2. import necessary modules as follows:
        
        ::
        
         from olsapy import olsa as ol
           
        3. generate a DataClass object as follows:
        
        ::
        
         dat = ol.DataClass()
        
        4. load the prepared data file into the generated object as follows:
        
        ::
        
         dat.load(<a path for the data file>)
        
        5. run OLSA and obtain a Result object as follows:
        
        ::
        
         res = ol.olsa(dat)
        
        6. export each result as csv files as follows:
        
        ::
        
         res.export()
        
        7. each result can be extracted as a dataframe if necessary as follows:
        
        ::
        
         dataframe = res.rsm()
        
        * a sample code for running OLSA described below:
        
        ::
        
         from olsapy import olsa as ol
           
         filein = '<file path>'
        
         #run OLSA simply
         dat = ol.DataClass() #generate a DataClass object
         dat.load(filein) #load data
         res = ol.olsa(dat) #run OLSA and obtain a Result object
         res.export() #save data
        
         #run OLSA with some options
         df = res.rsm() #.rsm(), etc. extract stored data in a Result object as a dataframe
         dat2 = ol.DataClass()
         dat2.load_df(df) #load dataframe into a DataClass object
         res2 = ol.olsa(dat2,accumulation=0.5) #accumulation determines the vectors subjected to varimax rotation
         res2.export(CM=True,TS=False) #results to be exported can be chosen.
        
        Licence
        =======================================================
        This software is released under the MIT License, see LICENSE.
        
        Authors
        =======================================================
        Setsuo Kinoshita, Shotaro Maedera, and Tadahaya Mizuno
        
        References
        =======================================================
        http://www.ilincs.org/ilincs/
        
        Bug Report
        =======================================================
        If you would like to report any bugs about olsapy, don't hesitate to create an issue on github here, or email me: tadahaya@gmail.com
Keywords: olsa,usspca,profiling,omics,bioinformatics,profile data,transcriptome
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Win32 (MS Windows)
Classifier: Framework :: IPython
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
