{ "info": { "author": "gemelli development team", "author_email": "cmartino@eng.ucsd.edu", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "License :: OSI Approved :: BSD License", "Operating System :: MacOS :: MacOS X", "Operating System :: POSIX", "Operating System :: Unix", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3 :: Only", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Bio-Informatics", "Topic :: Software Development :: Libraries" ], "description": "[![Build Status](https://travis-ci.org/cameronmartino/gemelli.svg?branch=master)](https://travis-ci.org/cameronmartino/gemelli)\n[![Coverage Status](https://coveralls.io/repos/github/cameronmartino/gemelli/badge.svg?branch=master)](https://coveralls.io/github/cameronmartino/gemelli?branch=master)\n\n**gemelli is still being developed, so backwards-incompatible changes might occur.**\n**If you have any questions, feel free to contact the development team at cmartino at eng.ucsd.edu.**\n\n# gemelli\n\nGemelli is a tool box for running tensor factorization on sparse compositional omics datasets. Gemelli performs unsupervised dimensionality reduction of spatiotemporal microbiome data. The outlut of gemelli helps to resolve spatiotemporal subject variation and the biological features that separate them. \n\n## Installation\n\nTo install the most up to date version of deicode, run the following command\n\n # pip (only supported for QIIME2 >= 2018.8)\n pip install gemelli\n\n**Note**: that gemelli is not compatible with python 2, and is compatible with Python 3.4 or later. \n\n## Using gemelli inside [QIIME 2](https://qiime2.org/)\n\nA QIIME2 tutorial can be found [here](https://github.com/cameronmartino/gemelli/blob/master/ipynb/tutorials/QIIME2-jansson-ibd-tutorial.md).\n\n`Note: a more formal tutorial is coming soon.`\n\n```bash\n$qiime gemelli ctf --help\n\nUsage: qiime gemelli ctf [OPTIONS]\n\n Gemelli resolves spatiotemporal subject variation and the biological\n features that separate them. In this case, a subject may have several\n paired samples, where each sample may be a time point. The output is akin\n to conventional beta-diversity analyses but with the paired component\n integrated in the dimensionality reduction.\n\nInputs:\n --i-table ARTIFACT FeatureTable[Frequency]\n Input table in biom format. [required]\nParameters:\n --m-sample-metadata-file METADATA...\n (multiple Sample metadata file in QIIME2 formatting.\n arguments will be \n merged) [required]\n --p-individual-id-column TEXT\n Metadata column containing subject IDs to use for\n pairing samples. WARNING: if replicates exist for an\n individual ID at either state_1 to state_N, that\n subject will be mean grouped by default. [required]\n --p-state-column TEXT Metadata column containing state (e.g.,Time,\n BodySite) across which samples are paired. At least\n one is required but up to four are allowed by other\n state inputs. [required]\n --p-n-components INTEGER\n The underlying low-rank structure (suggested: 2 <\n rank < 10) [minimum 2] [default: 3]\n --p-min-sample-count INTEGER\n Minimum sum cutoff of sample across all features\n [default: 0]\n --p-min-feature-count INTEGER\n Minimum sum cutoff of features across all samples\n [default: 0]\n --p-max-iterations-als INTEGER\n Max number of Alternating Least Square (ALS)\n optimization iterations (suggested to be below 100;\n beware of overfitting) [minimum 1] [default: 25]\n --p-max-iterations-rptm INTEGER\n Max number of Robust Tensor Power Method (RTPM)\n optimization iterations (suggested to be below 100;\n beware of overfitting) [minimum 1] [default: 25]\n --p-n-initializations INTEGER\n The number of initialization vectors. Larger values\n willgive more accurate factorization but will be more\n computationally expensive [minimum 1] [default: 25]\n --m-feature-metadata-file METADATA...\n (multiple \n arguments will be \n merged) [optional]\nOutputs:\n --o-subject-biplot ARTIFACT PCoAResults % Properties('biplot')\n Compositional biplot of subjects as points and\n features as arrows. Where the variation between\n subject groupings is explained by the log-ratio\n between opposing arrows. WARNING: The % variance\n explained is spread over n-components and can be\n inflated. [required]\n --o-state-distance-matrix ARTIFACT\n DistanceMatrix A sample-sample distance matrix generated from the\n euclidean distance of the subject-state ordinations\n and itself. [required]\n --o-state-subject-ordination ARTIFACT SampleData[SampleTrajectory]\n A trajectory is an ordination that can be\n visualizedover time or another context. [required]\n --o-state-feature-ordination ARTIFACT FeatureData[FeatureTrajectory]\n A trajectory is an ordination that can be\n visualizedover time or another context. [required]\nMiscellaneous:\n --output-dir PATH Output unspecified results to a directory\n --verbose / --quiet Display verbose output to stdout and/or stderr\n during execution of this action. Or silence output if\n execution is successful (silence is golden).\n --citations Show citations and exit.\n --help Show this message and exit.\n\n```\n\n## Using gemelli as a standalone tool\n\n```bash\n$ gemelli cmartino$ gemelli --help\n\nUsage: gemelli [OPTIONS]\n\n Runs CTF with an rclr preprocessing step.\n\nOptions:\n --in-biom TEXT Input table in biom format. [required]\n --sample-metadata-file TEXT Sample metadata file in QIIME2 formatting.\n [required]\n --individual-id-column TEXT Metadata column containing subject IDs to use\n for pairing samples. WARNING: if replicates\n exist for an individual ID at either state_1\n to state_N, that subject will be mean grouped.\n [required]\n --state-column-1 TEXT Metadata column containing state (e.g.,Time,\n BodySite) across which samples are paired. At\n least one is required but up to four are\n allowed by other state inputs. [required]\n --output-dir TEXT Location of output files. [required]\n --n_components INTEGER The underlying low-rank structure (suggested:\n 1 < rank < 10) [minimum 2] [default: 3]\n --min-sample-count INTEGER Minimum sum cutoff of sample across all\n features [default: 0]\n --min-feature-count INTEGER Minimum sum cutoff of features across all\n samples [default: 5]\n --max_iterations_als INTEGER Max number of Alternating Least Square (ALS)\n optimization iterations (suggested to be\n below 100; beware of overfitting) [minimum 1]\n [default: 50]\n --max_iterations_rptm INTEGER Max number of Robust Tensor Power Method\n (RTPM) optimization iterations (suggested to\n be below 100; beware of overfitting) [minimum\n 1] [default: 50]\n --n_initializations INTEGER The number of initialization vectors. Larger\n values willgive more accurate factorization\n but will be more computationally expensive\n (suggested to be below 100; beware of\n overfitting) [minimum 1] [default: 50]\n --feature-metadata-file TEXT Feature metadata file in QIIME2 formatting.\n --state-column-2 TEXT Metadata column containing state (e.g.,Time,\n BodySite) across which samples are paired. At\n least one is required but up to four are\n allowed by other state inputs.\n --state-column-3 TEXT Metadata column containing state (e.g.,Time,\n BodySite) across which samples are paired. At\n least one is required but up to four are\n allowed by other state inputs.\n --state-column-4 TEXT Metadata column containing state (e.g.,Time,\n BodySite) across which samples are paired. At\n least one is required but up to four are\n allowed by other state inputs.\n --help Show this message and exit.\n\n```\n\n## Other Resources\n\nNamed after gemelli by alighiero boetti and also the pasta. \n\n[TenAls translated from Sewoong Oh](http://swoh.web.engr.illinois.edu/software/optspace/code.html)\n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "", "keywords": "", "license": "BSD-3-Clause", "maintainer": "gemelli development team", "maintainer_email": "cmartino@eng.ucsd.edu", "name": "gemelli", "package_url": "https://pypi.org/project/gemelli/", "platform": "", "project_url": "https://pypi.org/project/gemelli/", "project_urls": null, "release_url": "https://pypi.org/project/gemelli/0.0.4/", "requires_dist": [ "numpy (>=1.12.1)", "click", "pandas (>=0.10.0)", "scipy (>=0.19.1)", "nose (>=1.3.7)", "scikit-learn (>=0.18.1)", "scikit-bio (>0.5.3)", 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