Metadata-Version: 1.1
Name: pareidolia
Version: 0.4.4
Summary: Multi-sample change detection in Hi-C patterns
Home-page: https://github.com/cmdoret/pareidolia
Author: Cyril Matthey-Doret
Author-email: cyril.matthey-doret@pasteur.fr
License: MIT
Description: pareidolia
        ==========
        
        .. image:: https://img.shields.io/pypi/v/pareidolia.svg
            :target: https://pypi.python.org/pypi/pareidolia
            :alt: Latest PyPI version
        
        .. image:: https://github.com/koszullab/pareidolia/actions/workflows/python-package.yml/badge.svg
           :target: https://github.com/koszullab/pareidolia/actions/workflows/python-package.yml
           :alt: build
        
        .. image:: https://codecov.io/gh/koszullab/pareidolia/branch/master/graph/badge.svg
          :target: https://codecov.io/gh/koszullab/pareidolia
        
        Multi-sample change detection in Hi-C patterns
        
        Pareidolia for detects changes in intensities of a specific pattern (e.g. chromatin loops and domain borders) from Hi-C maps.
        It can be used to compare samples from different conditions and use multiple replicates to improve results.
        
        This toolkit exploits `Chromosight <https://github.com/koszullab/chromosight>`_ correlation maps, allowing the same method to detect changes in different Hi-C patterns (e.g. loops or borders).
        
        Usage
        -----
        
        Pareidolia can be used both as a python package and as a command line tool:
        
        .. code-block:: python
        
          import pareidolia.hic_utils as pah
          import chromosight.kernels as ck
          pah.change_detection_pipeline(
            ["ctrl1.cool", "ctrl2.cool", "treat1.cool", "treat2.cool"],
            ["control", "control", "treatment", "treatment"],
            kernel=ck.loops,
            subsample=True,
            n_cpus=8,
          )
        
        We can also use the CLI to execute the same instruction:
        
        .. code-block:: bash
        
          pareidolia -n 8 \
                     -k loops \
                     ctrl1.cool,ctrl2.cool,treat1.cool,treat2.cool \
                     control,control,treatment,treatment \
                     output.tsv
        
        Pareidolia can either detect changes *de-novo*, or compute the change intensity at a set of input positions.
        The input positions can be provided as a bed2d (=bedpe) file, containing a list of 2D genomic coordinates.
        This file can be provided with the `--bed2d-file` option on the CLI, or using the `bed2d_file` parameter in the python API.
        
        Padeidolia accepts chromosight kernels as kernel names. A list of valid kernels can be displayed using `chromosight list-kernels`.
        Alternatively, when using the API, an arbitrary 2D numpy array can be provided as kernels.
        
        Installation
        ------------
        
        Pareidolia is available on Pypi and can be installed using:
        
        .. code:: bash
        
          pip3 install --user pareidolia
        
        
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Operating System :: OS Independent
