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        "author": "Antonio Pedro Camargo",
        "author_email": "antoniop.camargo@gmail.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License (GPL)",
            "Natural Language :: English",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Bio-Informatics",
            "Topic :: Software Development :: Libraries"
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        "description": "# tspex\n\n- [Overview](#overview)\n- [Documentation](#documentation)\n- [Installation](#installation)\n- [Python API tutorial](#python-api-tutorial)\n- [Command-line interface](#command-line-interface)\n- [Examples](#examples)\n\n## Overview\n\ntspex is a tissue-specificity calculator tool. It provides both an easy-to-use object-oriented Python API and a command-line interface (CLI) for calculating a variety of tissue-specificity metrics from gene expression data.\n\ntspex features include:\n  - Twelve different tissue-specificity metrics.\n  - Integration with popular data analysis libraries, such as NumPy, SciPy, and pandas.\n  - Visualization functions.\n  - Support for Jupyter notebooks.\n\n## Documentation\n\nA complete documentation for tspex can be found at [https://apcamargo.github.io/tspex/](https://apcamargo.github.io/tspex/).\n\n## Installation\n\nThere are two ways to install tspex:\n\n- Using pip:\n\n```\npip install tspex\n```\n\n- Using conda:\n\n```\nconda install -c bioconda tspex\n```\n\n\n## Python API tutorial\n\nFor a detailed guide on how to use the Python API, please check the [Jupyter notebook tutorial](https://github.com/apcamargo/tspex/blob/master/docs/python_api.ipynb).\n\n\n## Command-line interface\n\ntspex can be executed from the command line using the `tspex` command. It takes an expression matrix file as input and outputs the computed tissue-specificity values.\n\n\n```\nusage: tspex [-h] [-l] [-d] [-t THRESHOLD] input_file output_file method\n\nCompute gene tissue-specificity from an expression matrix and save the output.\n\npositional arguments:\n  input_file            Expression matrix file in the TSV, CSV or Excel\n                        formats.\n  output_file           Output TSV file containing tissue-specificity values.\n  method                Tissue-specificity metric. Allowed values are:\n                        \"counts\", \"tau\", \"gini\", \"simpson\",\n                        \"shannon_specificity\", \"roku_specificity\", \"tsi\",\n                        \"zscore\", \"spm\", \"spm_dpm\", \"js_specificity\",\n                        \"js_specificity_dpm\".\n\noptional arguments:\n  -h, --help            show this help message and exit\n  -l, --log             Log-transform expression values. (default: False)\n  -d, --disable_transformation\n                        By default, tissue-specificity values are transformed\n                        so that they range from 0 (perfectly ubiquitous) to 1\n                        (perfectly tissue-specific). If this parameter is\n                        used, transformation will be disabled and each metric\n                        will have have a diferent range of possible values.\n                        (default: False)\n  -t THRESHOLD, --threshold THRESHOLD\n                        Threshold to be used with the \"counts\" metric. If\n                        another method is chosen, this parameter will be\n                        ignored. (default: 0)\n```\n\n### Examples\n\n- Using the `spm` metric to compute tissue-specificity values from a log-transformed expression matrix:\n\n```\ntspex --log gene_expression.tsv tspex_spm.tsv spm\n```\n\n- Using the `counts` method to compute tissue-specificity by counting the number of tissues in which the gene expression is greater than 10:\n\n```\ntspex --threshold 10 gene_expression.tsv tspex_counts.tsv counts\n```\n\n- Using the `zscore` without transformation to quantify tissue-specificity as the number of standard deviations away from the mean gene expression:\n\n```\ntspex --disable_transformation gene_expression.tsv tspex_zscore.tsv zscore\n```\n\n\n",
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        "license": "GNU General Public License v3.0",
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