{ "info": { "author": "Keiron O'Shea", "author_email": "", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Science/Research", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering" ], "description": "# pyMEAN: Metabolomic Enrichment ANalysis in Python\n\nThe pyMEAN package is designed to facilitate semi-automated enrichment analysis for metabolomic experiments.\n\n## Installation\n\npyMEAN requires Python 3+ and is unfortunately not compatible with Python 2. If you are still using Python 2, a clever workaround is to install Python 3 and use that instead.\n\nThe easiest way of installing pyMEAN is using pip:\n\n```\npip install pymean\n```\n\nAlternatively, you can use git and pip in unison to get the development branch:\n\n```\npip install https://github.com/KeironO/pyMEAN\n```\n\n## Usage\n\nHere's a starting template to get you started:\n\n```python\n# Import pyMEAN module into Python.\nfrom pymean import EnrichmentAnalysis\n\n# A compound list of inchikeys.\ncompound_list = [\n \"WDJHALXBUFZDSR-UHFFFAOYSA-N\", # acetoacetic acid\n \"UCMIRNVEIXFBKS-UHFFFAOYSA-N\", # beta-alanine\n \"CVSVTCORWBXHQV-UHFFFAOYSA-N\", # creatine\n \"FFDGPVCHZBVARC-UHFFFAOYSA-N\", # dimethylglycine\n \"VZCYOOQTPOCHFL-OWOJBTEDSA-N\", # fumaric acid\n \"DHMQDGOQFOQNFH-UHFFFAOYSA-N\", # glycine\n \"FFFHZYDWPBMWHY-UHFFFAOYSA-N\", # l-homocysteine\n \"XUJNEKJLAYXESH-REOHCLBHSA-N\", # l-cysteine\n \"COLNVLDHVKWLRT-QMMMGPOBSA-N\", # l-phenylalanine\n \"BTNMPGBKDVTSJY-UHFFFAOYSA-N\" # phenylpyruvic acid\n]\n\n\n# Create an EnrichmentAnalysis object for the analysis of hsa\nea = EnrichmentAnalysis(compound_list, organism=\"hsa\")\n\n# Run the analysis\nea.run_analysis(pvalue_cutoff=0.05)\n\n# Obtain results (in the format of a pandas dataframe)\nresuklts = ea.results\n\n```\n\nIf you'd like to plot out your results, take inspiration from the following method:\n\n```python\ndef plot_enrichment_analysis_results(results: pd.DataFrame, adj_method:str):\n fold_enrichment = np.abs(np.log(results[\"%s adj. p-value\" % (adj_method)]))\n plt.figure()\n plt.title(\"Metabolite Sets Enrichment Overview\")\n plt.barh(results[\"Pathway Name\"], fold_enrichment, height=0.5)\n plt.xlabel(\"Fold Enrichment\")\n\n plt.yticks(fontsize=6)\n plt.tight_layout()\n\n plt.show()\n\nplot_enrichment_analysis_results(results, \"fdr_bh\")\n\n```\n\nWhich will return the following chart:\n\n![Plot of results](https://github.com/AberystwythSystemsBiology/pyMEAN/raw/master/example.png)\n\n## License\n\nCode released under the [GPLv3](https://github.com/AberystwythSystemsBiology/pyMEAN/blob/master/LICENSE).", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/AberystwythSystemsBiology/pyMEAN", "keywords": "metabolomics,enrichment analysis,omics", "license": "", "maintainer": "", "maintainer_email": "", "name": "pymean", "package_url": "https://pypi.org/project/pymean/", "platform": "", "project_url": "https://pypi.org/project/pymean/", "project_urls": { "Homepage": "https://github.com/AberystwythSystemsBiology/pyMEAN" }, "release_url": "https://pypi.org/project/pymean/0.30/", "requires_dist": null, "requires_python": ">= 3.6", "summary": "The pyMEAN package is designed to facilitate semi-automated enrichment analysis for metabolomic experiments.", "version": "0.30" }, "last_serial": 5484362, "releases": { "0.2": [ { "comment_text": "", "digests": { "md5": "27739b81d6fd324f4f6daa9baf54ba1d", "sha256": "c736ded50175de0d9cbe98cfcc311fc734878598e76b4f3768496422e00e7b48" }, "downloads": -1, "filename": "pymean-0.2.tar.gz", "has_sig": false, "md5_digest": "27739b81d6fd324f4f6daa9baf54ba1d", "packagetype": "sdist", "python_version": "source", "requires_python": ">= 3.6", "size": 18062, "upload_time": "2019-06-18T16:45:19", "url": "https://files.pythonhosted.org/packages/91/6d/f7bc3742897bb49f93a4101348a531e8c3e0389d22e403a291f9457780f2/pymean-0.2.tar.gz" } ], "0.21": [ { "comment_text": "", "digests": { "md5": "3dd52978f9cc29dfede30ae7c0e42663", "sha256": "fddd0c719ac20f8682455db2c0d832229e85d0c1873f0e2cc70b888a14643c4d" }, "downloads": -1, "filename": "pymean-0.21.tar.gz", "has_sig": false, "md5_digest": "3dd52978f9cc29dfede30ae7c0e42663", "packagetype": "sdist", "python_version": "source", "requires_python": ">= 3.6", "size": 18058, "upload_time": "2019-06-19T14:06:49", "url": "https://files.pythonhosted.org/packages/9a/2b/7c39830a50ee655af186cb5f4bb96946fe2951922980a0cd5460d575abf8/pymean-0.21.tar.gz" } ], "0.22": [ { "comment_text": "", "digests": { "md5": "95c2887751c1f9c90e28fa910a015c1a", "sha256": "9444533cd863c6a4ed46e771138a3223a0d22cec715aafdd2440c6394b8c5d3f" }, "downloads": -1, "filename": "pymean-0.22.tar.gz", "has_sig": false, "md5_digest": "95c2887751c1f9c90e28fa910a015c1a", "packagetype": "sdist", "python_version": "source", "requires_python": ">= 3.6", "size": 18172, "upload_time": "2019-06-19T15:10:52", "url": "https://files.pythonhosted.org/packages/a8/94/30c87e6b244ff1aee2d9a23ac9027799c792fee751480da63f4789cfc313/pymean-0.22.tar.gz" } ], "0.30": [ { "comment_text": "", "digests": { "md5": "b7183434094b1c23e48b9b1d782d189f", "sha256": "51fe958ca755bc24c302d01c9437dbc2db5b523092a6c885d83ea48bad517430" }, "downloads": -1, "filename": "pymean-0.30.tar.gz", "has_sig": false, "md5_digest": "b7183434094b1c23e48b9b1d782d189f", "packagetype": "sdist", "python_version": "source", "requires_python": ">= 3.6", "size": 18314, "upload_time": "2019-07-04T02:29:08", "url": "https://files.pythonhosted.org/packages/fe/7d/976c4ab634efa4b1feeccc05136b7b51606961c326ccd96962e82db7966a/pymean-0.30.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "b7183434094b1c23e48b9b1d782d189f", "sha256": "51fe958ca755bc24c302d01c9437dbc2db5b523092a6c885d83ea48bad517430" }, "downloads": -1, "filename": "pymean-0.30.tar.gz", "has_sig": false, "md5_digest": "b7183434094b1c23e48b9b1d782d189f", "packagetype": "sdist", "python_version": "source", "requires_python": ">= 3.6", "size": 18314, "upload_time": "2019-07-04T02:29:08", "url": "https://files.pythonhosted.org/packages/fe/7d/976c4ab634efa4b1feeccc05136b7b51606961c326ccd96962e82db7966a/pymean-0.30.tar.gz" } ] }