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        "author": "Zhemin Zhou",
        "author_email": "zhemin.zhou@warwick.ac.uk",
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        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7"
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        "description": "# Strain Prediction and Analysis using Representative SEquences (SPARSE)\n\nSPARSE indexes >100,000 reference genomes in public databases in to hierarchical clusters and uses it to predict origins of metagenomic reads. \n\n\n[![Build Status](https://travis-ci.org/zheminzhou/SPARSE.svg?branch=master)](https://travis-ci.org/zheminzhou/SPARSE)\n[![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)\n[![Docs Status](https://readthedocs.org/projects/sparse/badge/)](http://sparse.readthedocs.io/en/latest/)\n\n## Installation \n\nSPARSE runs on Unix and requires Python version 2.7 (Python 3.x supports are under development)\n\n**System modules (Ubuntu 16.04) :**\n\n* pip\n* gfortran\n* llvm\n* libncurses5-dev\n* cmake\n* xvfb-run (for malt, optional)\n\n**3rd-party software:**\n* samtools (>=1.2)\n* mash (>=1.1.1)\n* bowtie2 (>=2.3.2)\n* malt (>=0.4.0) (optional)\n\nSee [requirements.txt](requirements.txt) for python module dependencies. \n\n### Installation via PIP [Suggested]\n\n    pip install meta-sparse\n\n### Installation from source codes (Ubuntu) \n     \n    sudo apt-get update\n    sudo apt-get install gfortran llvm libncurses5-dev cmake python-pip samtools bowtie2\n    git clone https://github.com/zheminzhou/SPARSE\n    cd SPARSE/EM && make\n    pip install -r requirements.txt \n    \n\n### Updating SPARSE\nYou can update to latest version using PIP:\n```\npip install --upgrade meta-sparse\n```\nIf you installed SPARSE from github, move to installation directory and pull the latest version:  \n\n    cd SPARSE\n    git pull\n    \n    \n## Quick Start\nSee http://sparse.readthedocs.io/en/latest/ for full documentation.\n\n1. **Download reference database**\n\nWe provide a pre-compiled database based on RefSeq (dated 19.05.2018) to download at http://enterobase.warwick.ac.uk/sparse/refseq_20180519.tar.gz\n. The database can be downloaded and unpacked by running:\n   ```\n    curl -o refseq_20180519.tar.gz http://enterobase.warwick.ac.uk/sparse/refseq_20180519.tar.gz\n    tar -vxzf refseq_20180519.tar.gz\n   ```\n   \n   This pre-compiled database is about 350GB and contains four default mapping databases, which can be specified in the next step: representative, subpopulation, Virus, Eukaryota.\n   \n   To update the database or build a costum database, please refer to the full documentation.\n   \n2. **Predict read origins**\n\nThis following command will map and evaluate all reads in both fastq-files against the specified mapping databases. \n```\nsparse predict --dbname refseq_20180519 --mapDB representative,subpopulation,Virus,Eukaryota --r1 read1.fq.gz --r2 read2.fq.gz --workspace <workspace_name>\n```\nFor single-end reads, only --r1 needs to be specified. All output files are stored in the respective workspace.\n\n3. **Create a report**\n```\nsparse report <workspace_name>\n```\nThe report will be stored in <workspace_name>/profile.txt\n\n4. **Extract reference specific reads**\n\nThe following command extracts all reads specific to the provided reference ids, which can be found in the output of step 2.\n```\nsparse extract --dbname refseq_20171014 --workspace <workspace_name> --ref_id <comma delimited indices>\n```\n\n\n\n## Citation\nSPARSE is published as a conference proceeding in \"Research in Computational Molecular Biology\".\n\nZhemin Zhou, Nina Luhmann, Nabil-Fareed Alikhan, Christopher Quince, Mark Achtman, 'Accurate Reconstruction of Microbial Strains from Metagenomic Sequencing Using Representative Reference Genomes' RECOMB 2018: Research in Computational Molecular Biology pp 225-240. doi: https://doi.org/10.1007/978-3-319-89929-9_15\n\nA preprint version of the manuscript is also accessible in bioRxiv: https://doi.org/10.1101/215707",
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