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    "info": {
        "author": "An-Ni Zhang",
        "author_email": "anniz44@mit.edu",
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        "description": "# arg_ranker\n\n## Install\n`pip install arg_ranker`\n\n`conda install -c caozhichongchong arg_ranker`\n\n## Test (download examples and use any of these commands)\n`arg_ranker -i example/ARGprofile_example_1.txt -m example/metadata.txt`\\\n`arg_ranker -i example/ARGprofile_example_2.txt -m example/metadata.txt`\\\n`arg_ranker -i test`\n\n## How to use it\n### Prepare your ARG profile\n\narg_ranker is suitable for the units of ppm, gene copy per 16S or gene copy per cell\n\n#### Option 1: Use our pipeline\n\n1. Use my traits_finder to search ARGs in genomes and metagenomes (in preparation)\\\nNow we have both nucleotides and amino acids databases!\\\nhttps://github.com/caozhichongchong/traits_finder\n\n2. Run\\\n`arg_ranker -i ARG.profile.txt -m metadata.txt`\\\n`arg_ranker -i ARG.profile.txt`\n\n#### Option 2: Run your own pipeline using our database\n\n1. Search ARGs-OAP v1.0 database (amino acids) in your data using diamond or blast\\\nhttps://github.com/caozhichongchong/arg_ranker/tree/master/arg_ranker/data/SARG.db.fasta*\n\n2. Format your results into example/ARGprofile_example_1.txt or example/ARGprofile_example_2.txt\n\n3. Run\\\n`arg_ranker -i ARG.profile.txt -m metadata.txt`\\\n`arg_ranker -i ARG.profile.txt`\\\nIf you see a lot of errors saying: \"ARGs in mothertable do not match with the ARGs in ARG_rank.txt.\\\nPlease check something something in ARG.summary.cell.txt!\"\\\nIt means that the samples are placed as row names instead of colomn names (which arg_ranker expects).\\\nDon't worry, please try: `arg_ranker -i ARG.profile.txt.t`\\\nAs we automatically transpose your table to make it work.\n\n#### Option 3: Use results from ARGs-OAP v1.0 (not recommended)\n\n1. If you have already run the ARGs-OAP v1.0 pipeline\\\n    https://github.com/biofuture/Ublastx_stageone/archive/Ublastx_stageone.tar.gz\\\n    https://github.com/biofuture/Ublastx_stageone/archive/Ublastx_stageone.zip\n\n2. Check the \"extracted.fa.blast6out.txt\" and \"meta_data_online.txt\" in the output_dir\n\n3. Run\\\n`arg_ranker -f True -fo output_dir`\\\n`arg_ranker -i formated_table.normalize_cellnumber.gene.tab -m metadata.txt`\n\n### Prepare your metadata for your samples (optional)\n\nFormat your metadata of metagenomic samples into example/metadata.txt (not necessarily the same)\\\nFirst column matches the sample ID in your ARG profile;\\\nOther columns contain the metadata of your samples (such as habitat/eco-type, accession number, group...)\n\n## Introduction\nARG_ranker evaluates the risk of antibiotic resistance in metagenomes.\\\nWe designed a framework to rank the risk of ARGs based on three factors: \u201canthropogenic enrichment\u201d, \u201cmobility\u201d, and \u201chost pathogenicity\u201d, informed by all available bacterial genomes, plasmids, integrons, and 850 metagenomes covering diverse global eco-habitats. The framework prioritizes 3% of ARGs in Rank I (the most at risk of dissemination among pathogens) and 0.3% of ARGs in Rank II (high potential emergence of new resistance in pathogens). \n\nRequirement: python packages (pandas, argparse)\n\nRequirement: a mothertable of the ARG abundance in all your samples\nannotated by ARGs-OAP v1.0 \\\n(see example/All_sample_cellnumber.txt).\n\nOptimal: a table of the metadata of your samples \\\n(see example/All_sample_metadata.txt).\n\n## Copyright\nDr. An-Ni Zhang (MIT), Prof. Eric Alm (MIT), Prof. Tong Zhang* (University of Hong Kong)\n\n## Citation\n1. Zhang AN, ..., Alm EJ, Zhang T: Choosing Your Battles: Which Resistance Genes Warrant Global Action? (bioRxiv coming soon)\n2. Yang Y, ..., Tiedje JM, Zhang T: ARGs-OAP: online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database. Bioinformatics 2016.\n\n## Contact\nanniz44@mit.edu or caozhichongchong@gmail.com\n",
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        "keywords": "antibiotic resistance",
        "license": "MIT",
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        "summary": "Ranking the risk of antibiotic resistance for metagenomes",
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