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        "author": "Laurent Modolo",
        "author_email": "laurent.modolo@ens-lyon.fr",
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        "classifiers": [
            "License :: OSI Approved :: CEA CNRS Inria Logiciel Libre License, version 2.1 (CeCILL-2.1)",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
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        "description": "# IDR\n\nThis tool is designed to compute the Irreproducible Discovery Rate (IDR)\nfrom NarrowPeaks files for two or more replicates.\nIt\u2019s an implementation of the method described in the following paper using\nGaussian copula.\n\n> LI, Qunhua, BROWN, James B., HUANG, Haiyan, et al. Measuring reproducibility\n> of high-throughput experiments. The annals of applied statistics, 2011,\n> vol. 5, no 3, p. 1752-1779.\n\n## Getting Started\n\nThese instructions will get you a copy of the project up and running on your\nlocal machine for development and testing purposes.\n\n### Prerequisites\n\nTo run **midr** on your computer you need to have python (>= 3) installed.\n\n```sh\npython3 --version\n```\n\n### Installing\n\nTo easily install **midr** on your computer using `pip` run the following command:\n\n```\npip3 install midr\n```\n\nOtherwise you can clone this repository:\n\n```\ngit clone https://github.com/LBMC/midr.git\ncd midr/src/\npython3 setup.py install\n```\n\nGiven a list of peak calls in NarrowPeaks format and the corresponding peak\ncall for the merged replicate. This tool computes and appends a IDR column to\nNarrowPeaks files.\n\n### Dependencies\n\nThe **idr** package depends on the following python3 library:\n\n- [scipy>=1.3](https://scipy.org) [DOI:10.1109/MCSE.2007.58](https://doi.org/10.1109/MCSE.2007.58) [DOI:10.1109/MCSE.2011.36](https://doi.org/10.1109/MCSE.2011.36)\n\n> Travis E. Oliphant. Python for Scientific Computing, Computing in Science &\n> Engineering, 9, 10-20 (2007), DOI:10.1109/MCSE.2007.58\n\n> K. Jarrod Millman and Michael Aivazis. Python for Scientists and Engineers,\n> Computing in Science & Engineering, 13, 9-12 (2011),\n> DOI:10.1109/MCSE.2011.36\n\n\n- [numpy>=1.16](https://numpy.org/) [DOI:10.1109/MCSE.2011.37](https://doi.org/10.1109/MCSE.2010.118)\n\n> Travis E, Oliphant. A guide to NumPy, USA: Trelgol Publishing, (2006).\n\n> St\u00e9fan van der Walt, S. Chris Colbert and Ga\u00ebl Varoquaux. The NumPy Array:\n> A Structure for Efficient Numerical Computation, Computing in Science &\n> Engineering, 13, 22-30 (2011), DOI:10.1109/MCSE.2011.37\n\n- [matplotlib>=3.1](https://github.com/matplotlib/matplotlib/tree/v3.1.1) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3264781.svg)](https://doi.org/10.5281/zenodo.3264781)\n\n>  J. D. Hunter, \"Matplotlib: A 2D Graphics Environment\",\n> Computing in Science & Engineering, vol. 9, no. 3, pp. 90-95, 2007.\n\n- [pandas>=0.25.0](https://pandas.pydata.org)\n> McKinney. Data Structures for Statistical Computing in Python, Proceedings\n> of the 9th Python in Science Conference, 51-56 (2010) [(publisher link)](http://conference.scipy.org/proceedings/scipy2010/mckinney.html)\n\n- [pynverse>=0.1](https://pypi.org/project/pynverse/)\n\n## Usage\n\n**idr** Takes as input file in the [NarrowPeaks format](https://genome.ucsc.edu/FAQ/FAQformat.html#format12),\nand output NarrowPeaks files with an additional *idr* column.\n\nComputing *IDR* between three replicates\n\n```\n$ midr -m merged_peak_calling.NarrowPeaks \\\n     -f replicate1_.NarrowPeaks replicate2.NarrowPeaks replicate3.NarrowPeaks \\\n     -o results\n```\n\nWhere `replicate1_.NarrowPeaks` is the output of the peak caller on the \nalignment file corresponding to the first replicate and \n`merged_peak_calling.NarrowPeaks` is the output of the peak caller on the merge\nof the replicates alignment files.\n`Results` are the directory where we want to output our results.\n\nDisplaying help:\n\n```\n$ midr -h\nusage: midr [-h] --merged FILE --files FILES [FILES ...] [--output DIR]       \n           [--score SCORE_COLUMN] [--threshold THRESHOLD] [--debug]           \n           [--verbose]                                                        \n\nCompute the Irreproducible Discovery Rate (IDR) from NarrowPeaks files        \n\nImplementation of the IDR methods for two or more replicates.                 \n\nLI, Qunhua, BROWN, James B., HUANG, Haiyan, et al. Measuring reproducibility  \nof high-throughput experiments. The annals of applied statistics, 2011,       \nvol. 5, no 3, p. 1752-1779.                                                   \n\nGiven a list of peak calls in NarrowPeaks format and the corresponding peak   \ncall for the merged replicate. This tool computes and appends a IDR column to  \nNarrowPeaks files.                                                            \n\noptional arguments:                                                           \n  -h, --help            show this help message and exit                       \n\nIDR settings:                                                                 \n  --merged FILE, -m FILE                                                      \n                        file of the merged NarrowPeaks                        \n  --files FILES [FILES ...], -f FILES [FILES ...]                             \n                        list of NarrowPeaks files                             \n  --output DIR, -o DIR  output directory (default: results)                   \n  --score SCORE_COLUMN, -s SCORE_COLUMN                                       \n                        NarrowPeaks score column to compute the IDR on, one of\n                        'score', 'signalValue', 'pValue' or 'qValue' (default:\n                        signalValue)                                          \n  --threshold THRESHOLD, -t THRESHOLD                                         \n                        Threshold value for the precision of the estimator    \n                        (default: 0.01)                                       \n  --debug, -d           enable debugging (default: False)                     \n  --verbose             log to console (default: False)                       \n```\n\n\n## Authors\n\n* **Laurent Modolo** - *Initial work*\n\n## License\n\nThis project is licensed under the CeCiLL License- see the [LICENSE](LICENSE) file for details.\n\n\n",
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