Metadata-Version: 2.1
Name: serpentine
Version: 0.1.2
Summary: Serpentine binning package for Hi-C contact maps
Home-page: https://github.com/koszullab/serpentine
Author: vittore.scolari@pasteur.fr
License: Artistic License 2.0
Description: ![Serpentine logo](demos/serpentine.gif)
        
        # Serpentine binning
        
        [![PyPI version](https://badge.fury.io/py/serpentine.svg)](https://badge.fury.io/py/serpentine)
        ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/serpentine.svg)
        [![Build Status](https://travis-ci.org/koszullab/serpentine.svg?branch=master)](https://travis-ci.org/koszullab/serpentine)
        [![Appveyor Status](https://ci.appveyor.com/api/projects/status/github/koszullab/serpentine?svg=true)](https://ci.appveyor.com/project/baudrly/serpentine)
        [![codecov](https://codecov.io/gh/koszullab/serpentine/branch/master/graph/badge.svg)](https://codecov.io/gh/koszullab/serpentine)
        [![Read the docs](https://readthedocs.org/projects/serpentine/badge)](https://serpentine.readthedocs.io)
        [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/koszullab/serpentine/master?filepath=doc%2Fnotebooks%2Fdemo_yeast.ipynb)
        [![License: Artistic-2.0](https://img.shields.io/badge/License-Artistic%202.0-0298c3.svg)](https://opensource.org/licenses/Artistic-2.0)
        [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
        
        Locally smearing noisy regions in Hi-C contact maps as a prelude to differential analyses
        
        ## Table of contents
        
           - [Synopsis](#synopsis)
           - [Installation](#installation)
           - [Documentation](#documentation)
           - [Authors](#authors)
           - [Copyright and license](#copyright-and-license)
        
        ## Synopsis
        
        Use it as a Python 3 library:
        
        ```python
           import numpy as np
           import serpentine as sp
        
           A = np.loadtxt('./demos/A.csv')
           B = np.loadtxt('./demos/B.csv')
           trend, threshold = sp.MDbefore(A, B, show=False)
        
           sA, sB, sK = sp.serpentin_binning(A, B, threshold, threshold / 5)
        ```
        
        Or as a standalone UNIX tool:
        
        ```
        $ serpentine --help
           Serpentine binning
        
           An implementation of the so-called 'serpentine binning' procedure described
           in Scolari et al.
        
           Command line::
        
            Usage:
                serpentine.py [<matrixA>] [<matrixB>] [--threshold=auto] [--verbose]
                              [--min-threshold=auto] [--trend=high] [--triangular]
                              [--limit=3] [--demo] [--demo-size=500]
        
            Arguments:
                matrixA                         The first input matrix, in plain text
                                                CSV format. Optional in demo mode.
                matrixB                         The second input matrix, in plain text
                                                CSV format. Optional in demo mode or
                                                single binning mode.
        
            Options:
                -h, --help                      Display this help message.
                --version                       Display the program's current version.
                -t auto, --threshold auto       Threshold value to trigger binning.
                                                [default: auto]
                -m auto, --min-threshold auto   Minimum value to force trigger binning
                                                in either matrix. [default: auto]
                --trend high                    Trend to subtract to the differential
                                                matrix, possible values are "mean":
                                                equal amount of positive and negative
                                                differences, and "high": normalize
                                                at the regions with higher coverage.
                                                [default: high]
                --triangular                    Treat the matrix as triangular,
                                                useful when plotting matrices adjacent
                                                to the diagonal. [default: False]
                --limit 3                       Set the z-axis limit on the
                                                plot of the differential matrix.
                                                [default: 3]
                --demo                          Run a demo on randomly generated
                                                matrices. [default: False]
                --demo-size 500                 Size of the test matrix for the demo.
                                                [default: 500]
                -v, --verbose                   Show verbose output. [default: False]
        ```
        
        ## Installation
        
        ```sh
           sudo pip3 install -e git+https://github.com/koszullab/serpentine.git@master#egg=serpentine
        ```
        
        ## Documentation
        
        Executing the command `serpentine  --help` will give you a brief help of the command line tool. For a detailed reference to the python library functions, please 
        read the [documentation](https://serpentine.readthedocs.io/en/latest/).
        
        ## Authors
        
        Cluster Buster ([scovit](https://github.com/scovit), a.k.a. Vittore F. Scolari),
        Lyamovich ([baudrly](https://github.com/baudrly), a.k.a. Lyam Baudry)
        
        ## Copyright and license
        
        Copyright © 2017 Institut Pasteur, this software has been developed in
        the Regulation Spatiale des Chromosomes team of Pasteur Institut,
        Paris, France.
        
        This library is free software; you can redistribute it and/or modify
        it under the Artistic License.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Artistic License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
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: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Requires-Python: >=3.4
Description-Content-Type: text/markdown
