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        "description": "<p align=\"center\">\n<img src=\"logo/logo.png\">\n</p>\n\n[![Build Status](https://travis-ci.com/geronimp/enrichM.svg?branch=master)](https://travis-ci.com/geronimp/enrichM)\n[![Downloads](https://pepy.tech/badge/enrichm/month)](https://pepy.tech/project/enrichm/month)\n[![version status](https://img.shields.io/pypi/v/enrichm.svg)](https://pypi.python.org/pypi/enrichm)\n\nEnrichM is a set of comparative genomics tools for large sets of metagenome assembled genomes (MAGs). The current functionality includes:\n\n1. An basic annotation pipeline for MAGs.\n2. A pipeline to determine the metabolic pathways that are encoded by MAGs, using KEGG modules as a reference (although custom pathways can be specified)\n3. A pipeline to identify genes or metabolic pathways that are enriched within and between user-defined groups of genomes (groups can be genomes that are related functionally, phylogenetically, recovered from different environments, etc).\n4. To construct metabolic networks from annotated population genomes.\n5. Construct random forest machine learning models from the functional composition of either MAGs, metagenomes or transcriptomes.\n6. Apply these random forest machine learning models to classify new MAGs metagenomes.\n\nEnrichM is under active development, so there is no guaratee that master is stable. It's reccomended that EnrichM is downloaded either via pypi or conda (see below).\n\n# Installation\n## Dependencies\nEnrichM is written in python 3, and required >v3.6 to run. EnrichM requires the following non-python dependencies:\n* [hmmer](http://hmmer.org/) >= 3.1b\n* [seqmagick](https://fhcrc.github.io/seqmagick/) >= 0.6.1\n* [diamond](https://github.com/bbuchfink/diamond) == 0.9.22\n* [prodigal](http://prodigal.ornl.gov/) >= 2.6.3\n* [parallel](https://www.gnu.org/software/parallel/) >= 20180222\n* [mmseqs](https://github.com/soedinglab/MMseqs2) >= 2-23394\n* [R](https://www.r-project.org/) >= 3.0.1\n* [mcl](https://micans.org/mcl/) >= 14-137\n\n## PyPi\nInstall from PyPi like this:\n```\nsudo pip3 install enrichm\n```\n\n## conda (recommended)\nInstall the conda package like so:\n```\n# Create a python3 environment for EnrichM. Replace \"X.X.X\" with the version number\nconda create -n enrichm_X.X.X python=3\n# Activate that environment once it has compiled\nsource activate enrichm_X.X.X\n# Install EnrichM's dependencies\nconda install -c bioconda mcl R hmmer diamond prodigal parallel openmp mmseqs2 moreutils\n# Install EnrichM itself\nconda install -c geronimp enrichm\n\n# Install R dependencies\nR\ninstall.packages(\u2018gridExtra\u2019)\ninstall.packages(\u2018optparse\u2019)\nq()\n```\nAfter this, you'll need to set up EnrichM to run by downloading its back end databases.\n\n# Setup\n## Loading EnrichM's database\nBefore running EnrichM, you'll need to download the back-end database. This file is large (5.7G) and contains all the reference databases EnrichM needs to annotate and compare your genomes. This includes Pfam-A HMMs, TIGRfam HMMs, a DIAMOND database of the sequences in uniref100 with EC and KO annotations, and KoFamKOALA HMMs. By default the database will be installed in your home directory. This is done using a command in EnrichM:\n```\nenrichm data\n```\nThis should take approximately 15 minutes. To check for updates and install updates, simply run the same command. You can uninstall the database, using:\n```\nenrichm data --uninstall\n```\n\n## Sepcifying the location of the EnrichM database\nIf you would like to store the EnrichM database outside of your home directory, move you need to tell EnrichM where to look. To do this, export a BASH variable named \"ENRICHM_DB\":\n\n```\nexport ENRICHM_DB=/path/to/database/\n```\n\nAfter which EnrichM should be able to find the database. It may be worthwhile putting this in your .bashrc so you dont have to re-run it every time you open a terminal.\n\n# Subcommands\n## annotate\nAnnotate is a function that allows you to annotate your population genomes with [KO](http://www.kegg.jp/kegg/ko.html), [PFAM](http://pfam.xfam.org/), [TIGRFAM](http://www.jcvi.org/cgi-bin/tigrfams/index.cgi), and CAZY using [dbCAN](cys.bios.niu.edu/dbCAN2). The result will be a .gff file for each genome, and a frequency matrix for each annotation type where the rows are annotation IDs and the columns are genomes.\n\nSee the [annotate help page](https://github.com/geronimp/enrichM/wiki/annotate) for more\n\n## classify\nClassify quickly reads in KO annotations in the form of a matrix (KO IDs as rows, genomes as columns) and determines which [KEGG modules](http://www.kegg.jp/kegg/module.html) are complete. Annotation matrices can be generated using the annotate function.\n\nSee the [classify help page](https://github.com/geronimp/enrichM/wiki/classify) for more\n\n## enrichment\nEnrichment will read in KO or PFAM annotations in the form of a matrix (IDs as rows, genomes as columns) and a metadata file that separates genomes into groups to compare, and will run some basic stats to determine the enrichment of modules or pfam clans between and within the groups.\n\nSee the [enrichment help page](https://github.com/geronimp/enrichM/wiki/enrichment) for more\n\n## pathway\nPathway reads in a KO matrix and generates a Cytoscape-readable metabolic network and metadata file. Only reactions that are possible given the KOs present in the input matrix are shown, and the modules and reactions that are included in the output can be customized.\n\nSee the [pathway help page](https://github.com/geronimp/enrichM/wiki/pathway) for more\n\n## explore\nExplore is similar to pathway, but rather than generating a specified pathway it will start from a given query compound ID, and explore the possible reactions that use that compound given the enzymes present in the input KO matrix.\n\nSee the [explore help page](https://github.com/geronimp/enrichM/wiki/explore) for more\n\n# Contact\nIf you have any feedback about EnrichM, drop an email to the [SupportM](https://groups.google.com/forum/?hl=en#!forum/supportm) public help forum. Software by [Joel A. Boyd](https://ecogenomic.org/personnel/mr-joel-boyd) (@geronimp) at the Australian Centre for Ecogenomics (ACE).\n\n# License\nEnrichM is licensed under the GNU GPL v3+. See LICENSE.txt for further details.\n\n# Contributing \nI want EnrichM to be as useful as possible, so please feel free to leave feature requests and bug reports.\n\n# Citation\nA manuscript is in the final stages of preparation and a bioRxiv pre-print will be up shortly. If you find EnrichM useful and use it in your work, please cite it as follows:\n```\nComparative genomics using EnrichM. Joel A Boyd Ben J Woodcroft Gene W Tyson. 2019. In preparation.\n```",
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