# MirMachine
[](https://app.travis-ci.com/sinanugur/MirMachine) [](https://mirmachine.readthedocs.io/en/latest/?badge=latest)
[](http://www.repostatus.org/#active) [](https://badge.fury.io/py/MirMachine) [](https://anaconda.org/bioconda/mirmachine) [](https://anaconda.org/bioconda/mirmachine)
[](https://anaconda.org/bioconda/mirmachine)
A command line tool to detect miRNA homologs in genome sequences.
Installation
------------
To install this package with conda run:
```
conda install mirmachine -c bioconda -c conda-forge
```
Please add conda-forge as a channel. Installing via [mamba](https://github.com/mamba-org/mamba) is also strongly recommended for a faster installation. You can install __mamba__ and later MirMachine like this:
```
conda install mamba -c conda-forge
mamba install mirmachine -c bioconda -c conda-forge
```
Check if the installation works by calling the main script.
```
MirMachine.py --help
```
Note: You have to install dependencies if you prefer GitHub or PyPi installation.
A warning for Apple Silicon users (e.g. M1 or M2): bedtools depedency is not available for arm64 architecture. You have to set your environment to osx-64. You can install like this, which create a new environment and will install MirMachine:
```
CONDA_SUBDIR=osx-64 mamba create -n mirmachine -c conda-forge -c bioconda mirmachine
```
Quick start example
-------------------
Create a new directory and run MirMachine there after the installation. MirMachine will create the required directories while running.
```
MirMachine.py -n Caenorhabditis -s Caenorhabditis_elegans --genome sample/genomes/ce11.fa --cpu 20
```
See our documentation for detailed explanations: https://mirmachine.readthedocs.io/
Options and Arguments
---------------------
```
Usage:
MirMachine.py --node <text> --species <text> --genome <text> [--model <text>] [--cpu <integer>] [--add-all-nodes|--single-node-only] [--unlock|--remove] [--dry]
MirMachine.py --species <text> --genome <text> --family <text> [--model <text>] [--unlock|--remove] [--dry]
MirMachine.py --node <text> [--add-all-nodes]
MirMachine.py --print-all-nodes
MirMachine.py --print-all-families
MirMachine.py --print-ascii-tree
MirMachine.py (-h | --help)
MirMachine.py --version
Arguments:
-n <text>, --node <text> Node name. (e.g. Caenorhabditis)
-s <text>, --species <text> Species name. (e.g. Caenorhabditis_elegans)
-g <text>, --genome <text> Genome fasta file location (e.g. data/genome/example.fasta)
-m <text>, --model <text> Model type: deutero, proto, combined [default: combined]
-f <text>, --family <text> Run only a single miRNA family (e.g. Let-7).
-c <integer>, --cpu <integer> CPUs. [default: 2]
Options:
-a, --add-all-nodes Move on the tree both ways.
-o, --single-node-only Run only on the given node for miRNA families.
-p, --print-all-nodes Print all available node options and exit.
-l, --print-all-families Print all available families in this version and exit.
-t, --print-ascii-tree Print ascii tree of the tree file.
-u, --unlock Rescue stalled jobs (Try this if the previous job ended prematurely).
-r, --remove Clear all output files (this won't remove input files).
-d, --dry Dry run.
-h, --help Show this screen.
--version Show version.
```
Output
------
The `MirMachine` main executable will generate GFF annotations (filtered and unfiltered) and some other files.
You will see `results/predictions/` directory which contains:
`gff/` __All predicted miRNA families.__
`filtered_gff/` __High confidence miRNA family predictions after bitscore filtering. (This file is what you need in most cases)__
`fasta/` __Both high and low confidence predictions in FASTA format.__
MirMachine's other repos
------
Web application repo: https://github.com/selfjell/MirMachine
Supplementary files repo: https://github.com/sinanugur/MirMachine-supplementary
Citiation
------
Our Cell Genomics paper is here: [https://doi.org/10.1016/j.xgen.2023.100348](https://doi.org/10.1016/j.xgen.2023.100348)
Please cite if you find our tool useful.
Raw data
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"description": "# MirMachine\n\n[](https://app.travis-ci.com/sinanugur/MirMachine) [](https://mirmachine.readthedocs.io/en/latest/?badge=latest) \n\n\n[](http://www.repostatus.org/#active) [](https://badge.fury.io/py/MirMachine) [](https://anaconda.org/bioconda/mirmachine) [](https://anaconda.org/bioconda/mirmachine) \n[](https://anaconda.org/bioconda/mirmachine) \nA command line tool to detect miRNA homologs in genome sequences.\n\n\nInstallation\n------------\nTo install this package with conda run:\n\n```\nconda install mirmachine -c bioconda -c conda-forge\n```\n\nPlease add conda-forge as a channel. Installing via [mamba](https://github.com/mamba-org/mamba) is also strongly recommended for a faster installation. You can install __mamba__ and later MirMachine like this:\n```\nconda install mamba -c conda-forge\nmamba install mirmachine -c bioconda -c conda-forge\n```\n\nCheck if the installation works by calling the main script. \n```\nMirMachine.py --help\n```\n\nNote: You have to install dependencies if you prefer GitHub or PyPi installation.\n\nA warning for Apple Silicon users (e.g. M1 or M2): bedtools depedency is not available for arm64 architecture. You have to set your environment to osx-64. You can install like this, which create a new environment and will install MirMachine:\n```\nCONDA_SUBDIR=osx-64 mamba create -n mirmachine -c conda-forge -c bioconda mirmachine\n```\n\nQuick start example\n-------------------\nCreate a new directory and run MirMachine there after the installation. MirMachine will create the required directories while running.\n```\nMirMachine.py -n Caenorhabditis -s Caenorhabditis_elegans --genome sample/genomes/ce11.fa --cpu 20\n```\n\nSee our documentation for detailed explanations: https://mirmachine.readthedocs.io/\n\nOptions and Arguments\n---------------------\n```\nUsage:\n MirMachine.py --node <text> --species <text> --genome <text> [--model <text>] [--cpu <integer>] [--add-all-nodes|--single-node-only] [--unlock|--remove] [--dry]\n MirMachine.py --species <text> --genome <text> --family <text> [--model <text>] [--unlock|--remove] [--dry]\n MirMachine.py --node <text> [--add-all-nodes]\n MirMachine.py --print-all-nodes\n MirMachine.py --print-all-families\n MirMachine.py --print-ascii-tree\n MirMachine.py (-h | --help)\n MirMachine.py --version\n\nArguments:\n -n <text>, --node <text> Node name. (e.g. Caenorhabditis)\n -s <text>, --species <text> Species name. (e.g. Caenorhabditis_elegans)\n -g <text>, --genome <text> Genome fasta file location (e.g. data/genome/example.fasta)\n -m <text>, --model <text> Model type: deutero, proto, combined [default: combined]\n -f <text>, --family <text> Run only a single miRNA family (e.g. Let-7).\n -c <integer>, --cpu <integer> CPUs. [default: 2]\n\nOptions:\n -a, --add-all-nodes Move on the tree both ways.\n -o, --single-node-only Run only on the given node for miRNA families.\n -p, --print-all-nodes Print all available node options and exit.\n -l, --print-all-families Print all available families in this version and exit.\n -t, --print-ascii-tree Print ascii tree of the tree file.\n -u, --unlock Rescue stalled jobs (Try this if the previous job ended prematurely).\n -r, --remove Clear all output files (this won't remove input files).\n -d, --dry Dry run.\n -h, --help Show this screen.\n --version Show version.\n```\n\nOutput\n------\nThe `MirMachine` main executable will generate GFF annotations (filtered and unfiltered) and some other files.\nYou will see `results/predictions/` directory which contains:\n\n`gff/` __All predicted miRNA families.__ \n`filtered_gff/` __High confidence miRNA family predictions after bitscore filtering. (This file is what you need in most cases)__ \n`fasta/` __Both high and low confidence predictions in FASTA format.__ \n\n\nMirMachine's other repos\n------\nWeb application repo: https://github.com/selfjell/MirMachine \nSupplementary files repo: https://github.com/sinanugur/MirMachine-supplementary\n\nCitiation\n------\nOur Cell Genomics paper is here: [https://doi.org/10.1016/j.xgen.2023.100348](https://doi.org/10.1016/j.xgen.2023.100348)\nPlease cite if you find our tool useful.\n\n\n",
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