{ "info": { "author": "A. Belcour", "author_email": "arnaud.belcour@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "Programming Language :: Python :: 3" ], "description": "AuCoMe: Automatic Comparison of Metabolism\n==========================================\n\nWorkflow to reconstruct multiple metabolic networks in order to compare them.\n\n.. contents:: Table of contents\n :backlinks: top\n :local:\n\n\nInstallation\n------------\n\nDocker\n~~~~~~\n\nFrom git repository:\n\n.. code:: sh\n\n\tgit clone https://github.com/AuReMe/aucome.git\n\n\tcd aucome\n\n\tdocker build .\n\nTo run annotation based reconstruction, you need to install Pathway-Tools. This tool is available at the [Pathway-Tools website](http://bioinformatics.ai.sri.com/ptools/). A command in the package install the tools:\n\n.. code:: sh\n\n aucome --installPWT=path/to/pathway/tools/installer\n\nYou can also provide an option to this commande: --ptools=ptools_path\n\nThis option let you choose the path where the ptools-local folder will be installed. PGDBs created by Pathway-Tools are stored in this folder.\n\npip\n~~~\n\nIf you have installed all the dependencies, you can just install acuome with:\n\n.. code:: sh\n\n\tpip install aucome\n\nUsage\n-----\n\nYou have to create the working folder for AuCoMe, with teh --init argument:\n\n.. code:: sh\n\n aucome --init=run_ID [-v]\n\nThis command will create a folder name \"run_ID\" inside the working folder. In this \"run_ID\" folder, the command will create all the folders used during the analysis.\n\n.. code-block:: text\n\n\trun_ID\n\t\u251c\u2500\u2500 analysis\n\t\t\u251c\u2500\u2500\n\t\u251c\u2500\u2500 annotation_based\n\t\t\u251c\u2500\u2500 PADMETs\n\t\t\t\u251c\u2500\u2500\n\t\t\u251c\u2500\u2500 PGDBs\n\t\t\t\u251c\u2500\u2500\n\t\t\u251c\u2500\u2500 SBMLs\n\t\t\t\u251c\u2500\u2500\n\t\u251c\u2500\u2500 config.txt\n\t\u251c\u2500\u2500 model_organisms\n\t\t\u251c\u2500\u2500\n\t\u251c\u2500\u2500 networks\n\t\t\u251c\u2500\u2500\n\t\u251c\u2500\u2500 orthology_based\n\t\t\u251c\u2500\u2500 Orthofinder_WD\n\t\t\t\u251c\u2500\u2500\n\t\u251c\u2500\u2500 studied_organisms\n\t\t\u251c\u2500\u2500\n\nanalysis will store the result of padmet analysis.\n\nannotation_based contains three sub-folders. The folder PGDBs will contain all the results from Pathway-Tools (in dat format). These results will be stored in padmet and sbml inside PADMETs and SBMLs.\n\nconfig.txt contains numerous paths used by the script.\n\nmodel_organisms contains the model organisms you want to use for the orthology. In this folder you put a new folder with the name of the species and in this folder you put the proteome and the sbml of the metabolic network of your species. Proteome and metabolic network names must be the same than the name of the folder.\n\n.. code-block:: text\n\n\t\u251c\u2500\u2500 model_organisms\n\t\t\u251c\u2500\u2500 A_thaliana\n\t\t\t\u251c\u2500\u2500 A_thaliana.fasta\n\t\t\t\u251c\u2500\u2500 A_thaliana.sbml\n\nnetworks will contain all the metabolic network created by aucome in padmet format.\n\northology_based contains one folder Orthofinder_WD. This folder will contain all the run of Orthofinder.\n\nstudied_organisms: you put all the species that you want to studies in this folder. For each species you create a folder and in this folder you put the genbank file of this species. Like for model_organisms, file and folder must have the same name. And the genbank file must end with a '.gbk'.\n\n.. code-block:: text\n\n\t\u251c\u2500\u2500 studied_organisms\n\t\t\u251c\u2500\u2500 species_1\n\t\t\t\u251c\u2500\u2500 species_1.gbk\n\t\t\u251c\u2500\u2500 species_2\n\t\t\t\u251c\u2500\u2500 species_2.gbk\n\n\nOnce you have put your species in the studied_organisms folder and teh model in model_organisms, a check must be done on the data using:\n\n.. code:: sh\n\n aucome check --run=run_ID [--cpu=INT] [-v]\n\nThis command will check if there is no character that will make some scritp crashed later in the analysis. It will also create the proteome fasta file from the genbank.\n\nAnd for the annotation_based folder, if PGDBs contains folder, it will create the padmet and the sbml corresponding to these draft in PADMETs and SBMLs.\n\nA run of Pathway-Tools can be launched using the command:\n\n.. code:: sh\n\n aucome reconstruction --run=run_ID [--cpu=INT] [-v]\n\nUsing the package mpwt, it will create the input file for Pathway-Tools inside studied_organisms and if there is no error, it will create for each species inside this folder a folder inside PGDBs containing all the dat files ofthe draft metabolic network.\n\nOrthofinder can be launched using:\n\n.. code:: sh\n\n\taucome orthology --run=run_ID [-S=STR] [--orthogroups] [--cpu=INT] [-v]\n\nThen the proteome from the studied organisms and from the models will be moved to the Orthofinder_WD folder and orthofinder will be launch on them. Orthofinder result will be in this folder and in orthology_based, there will be all the metabolic network reconstructed from orthology.\n\nThen you can merge all the metabolic network with:\n\n.. code:: sh\n\n aucome draft --run=run_ID [--cpu=INT] [-v]\n\nThis will output the result inside the networks folder.\n\nYou can launch the all workflow with the command:\n\n.. code:: sh\n\n aucome workflow --run=ID [-S=STR] [--orthogroups] [--cpu=INT] [-v]", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/AuReMe/aucome", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "aucome", "package_url": "https://pypi.org/project/aucome/", "platform": "", "project_url": "https://pypi.org/project/aucome/", "project_urls": { "Homepage": "https://github.com/AuReMe/aucome" }, "release_url": "https://pypi.org/project/aucome/0.0.4/", "requires_dist": null, "requires_python": "", "summary": "Automatic Comparison of Metabolism", "version": "0.0.4" }, "last_serial": 5446244, "releases": { "0.0.4": [ { "comment_text": "", "digests": { "md5": "3b17fe7baf9cd6aeb4c774e6fbf91d22", "sha256": "77b27bbf1c2b0729975e98a6752a3d97e9d130ef08b7081415628a416197353b" }, "downloads": -1, "filename": "aucome-0.0.4.tar.gz", "has_sig": false, "md5_digest": "3b17fe7baf9cd6aeb4c774e6fbf91d22", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 14317, "upload_time": "2019-06-25T14:44:35", "url": "https://files.pythonhosted.org/packages/33/20/5864aadc322f1d8c04dddfea2c691eb759022e4a25f10e922fa11b4d1ecf/aucome-0.0.4.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "3b17fe7baf9cd6aeb4c774e6fbf91d22", "sha256": "77b27bbf1c2b0729975e98a6752a3d97e9d130ef08b7081415628a416197353b" }, "downloads": -1, "filename": "aucome-0.0.4.tar.gz", "has_sig": false, "md5_digest": "3b17fe7baf9cd6aeb4c774e6fbf91d22", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 14317, "upload_time": "2019-06-25T14:44:35", "url": "https://files.pythonhosted.org/packages/33/20/5864aadc322f1d8c04dddfea2c691eb759022e4a25f10e922fa11b4d1ecf/aucome-0.0.4.tar.gz" } ] }