{ "info": { "author": "Unlearn.AI, Inc.", "author_email": "drckf@unlearn.ai", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering :: Bio-Informatics" ], "description": "genemunge\n=========\n\nTools for munging genomic data such as: - Converting between different\ntypes of gene identifiers - Searching for terms in the Gene Ontology\n(GO) associated with a keyword - Looking up housekeeping genes and\ntranscription factors - Getting a list of GO terms associated with a\ngiven gene - Looking up how a gene is expressed across tissues -\nNormalizing a matrix of gene expression data by converting to TPM\n\nUnlearn.AI\n----------\n\nWhen we\u2019re not developing super awesome open source packages like\n``genemunge``, we help biopharma partners use unsupervised deep learning\nto extract insights from their omics data. Learn more at\n`unlearn.health `__.\n\nInstall\n-------\n\nThis library is accompanied by the following data sources: - The `Gene\nOntology `__. The current version used here is\nthe 2018-03-27 release. -\n`recount2 `__ data for\nGTEx. - `HGNC `__ gene symbols. - A list of\n`transcription factors `__. - A list of\n`housekeeping genes `__.\n\nInstalling this package through ``pip`` (``pip install genemunge`` from PyPI,\n``pip install .`` from GitHub) will use the static data that accompanies this repository.\n\nIf you wish to use the latest data from the above sources, you may\ninstall in \"develop\" mode from GitHub with ``pip -e install .``. Notably, this will\ndownload and process the recount2 GTEx data, requiring ``R`` and the\n``recount`` package from ``bioconductor``:\n\n::\n\n source(\"https://bioconductor.org/biocLite.R\")\n biocLite(\"recount\")\n\nCitations\n---------\n\nPlease cite the following papers if you make use of genemunge for a\npublication.\n\nThis package:\n\nGene Ontology: Ashburner et al. Gene ontology: tool for the unification\nof biology (2000) Nat Genet 25(1):25-9 GO Consortium, Nucleic Acids\nRes., 2017\n\nrecount2: Collado-Torres L, Nellore A, Kammers K, Ellis SE, Taub MA,\nHansen KD, Jaffe AE, Langmead B, Leek JT. Reproducible RNA-seq analysis\nusing recount2. Nature Biotechnology, 2017.\n\nHGNC: Gray KA, Yates B, Seal RL, Wright MW, Bruford EA. genenames.org:\nthe HGNC resources in 2015. Nucleic Acids Res. 2015 Jan;43(Database\nissue):D1079-85.\n\nTranscription factors: TFcheckpoint: a curated compendium of specific\nDNA-binding RNA polymerase II transcription factors Konika Chawla;\nSushil Tripathi; Liv Thommesen; Astrid Laegreid; Martin Kuiper\nBioinformatics 2013.\n\nHousekeeping genes: E. Eisenberg and E.Y. Levanon, Trends in Genetics\n29, (2013)\n\nSimilar tools\n-------------\n\nIf you know of similar tools that would be helpful references for users,\nplease contribute an attribution to them here.\n\n1. `goatools `__\n2. `goenrich `__\n\nGO evidence codes\n-----------------\n\n::\n\n Experiment:\n - Inferred from Experiment (EXP)\n - Inferred from Direct Assay (IDA)\n - Inferred from Physical Interaction (IPI)\n - Inferred from Mutant Phenotype (IMP)\n - Inferred from Genetic Interaction (IGI)\n - Inferred from Expression Pattern (IEP)\n\n Computational:\n - Inferred from Sequence or structural Similarity (ISS)\n - Inferred from Sequence Orthology (ISO)\n - Inferred from Sequence Alignment (ISA)\n - Inferred from Sequence Model (ISM)\n - Inferred from Genomic Context (IGC)\n - Inferred from Biological aspect of Ancestor (IBA)\n - Inferred from Biological aspect of Descendant (IBD)\n - Inferred from Key Residues (IKR)\n - Inferred from Rapid Divergence(IRD)\n - Inferred from Reviewed Computational Analysis (RCA)\n\n Literature:\n - Traceable Author Statement (TAS)\n - Non-traceable Author Statement (NAS)\n\n Other:\n - Inferred by Curator (IC)\n - No biological Data available (ND) evidence code\n - Inferred from Electronic Annotation (IEA)\n\nCommon gene id types\n--------------------\n\n``['symbol','name','entrez_id','ensembl_gene_id','refseq_accession','uniprot_ids']``\n\n\n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://github.com/unlearnai/genemunge", "keywords": "bioinformatics genomics", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "genemunge", "package_url": "https://pypi.org/project/genemunge/", "platform": "", "project_url": "https://pypi.org/project/genemunge/", "project_urls": { "Homepage": "http://github.com/unlearnai/genemunge" }, "release_url": "https://pypi.org/project/genemunge/0.0/", "requires_dist": [ "h5py", "matplotlib", "numpy", "pandas", "pytest", "seaborn", "tables", "cytoolz" ], "requires_python": ">=3.5", "summary": "Tools for munging genomics data", "version": "0.0" }, "last_serial": 3778739, "releases": { "0.0": [ { "comment_text": "", "digests": { "md5": "6278cb2b17087aa1c760f1963f1d015b", "sha256": "11cb93b8aca312332c341fb53d4618d90222f3beecc44d1eaef5413e5f64f62b" }, "downloads": -1, "filename": "genemunge-0.0-py3-none-any.whl", "has_sig": false, "md5_digest": "6278cb2b17087aa1c760f1963f1d015b", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": ">=3.5", "size": 39435719, "upload_time": "2018-04-18T22:10:29", "url": "https://files.pythonhosted.org/packages/9c/28/211e1a7545aaffd492c967ec219076778350d4446c794685164604a157e7/genemunge-0.0-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "a0d26980a3f3a17e6114fabb3edc7159", "sha256": "997b5adc7892b8794c97a3113bdc8ddec4c89c229b5da563aafe64ceec13b9b7" }, "downloads": -1, "filename": "genemunge-0.0.tar.gz", "has_sig": false, "md5_digest": "a0d26980a3f3a17e6114fabb3edc7159", "packagetype": "sdist", "python_version": "source", "requires_python": ">=3.5", "size": 39193461, "upload_time": "2018-04-18T22:10:54", "url": "https://files.pythonhosted.org/packages/41/28/8d4e387510da28e8db22293296a3998c0b65ad926287f87947db73864d3a/genemunge-0.0.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "6278cb2b17087aa1c760f1963f1d015b", "sha256": "11cb93b8aca312332c341fb53d4618d90222f3beecc44d1eaef5413e5f64f62b" }, "downloads": -1, "filename": "genemunge-0.0-py3-none-any.whl", "has_sig": false, "md5_digest": "6278cb2b17087aa1c760f1963f1d015b", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": ">=3.5", "size": 39435719, "upload_time": "2018-04-18T22:10:29", "url": "https://files.pythonhosted.org/packages/9c/28/211e1a7545aaffd492c967ec219076778350d4446c794685164604a157e7/genemunge-0.0-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "a0d26980a3f3a17e6114fabb3edc7159", "sha256": "997b5adc7892b8794c97a3113bdc8ddec4c89c229b5da563aafe64ceec13b9b7" }, "downloads": -1, "filename": "genemunge-0.0.tar.gz", "has_sig": false, "md5_digest": "a0d26980a3f3a17e6114fabb3edc7159", "packagetype": "sdist", "python_version": "source", "requires_python": ">=3.5", "size": 39193461, "upload_time": "2018-04-18T22:10:54", "url": "https://files.pythonhosted.org/packages/41/28/8d4e387510da28e8db22293296a3998c0b65ad926287f87947db73864d3a/genemunge-0.0.tar.gz" } ] }