MirMachine
Project description
MirMachine
A command line tool to detect miRNA homologs in genome sequences.
Installation
To install this package with conda run:
conda install -c bioconda mirmachine
Alternative method:
git clone https://github.com/sinanugur/MirMachine.git
cd MirMachine
pip install .
Check if the installation works by calling the main script.
MirMachine.py --help
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 -m proto --cpu 20
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-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: proto]
-f <text>, --family <text> Run only a single miRNA family.
-c <integer>, --cpu <integer> CPUs. [default: 2]
Options:
-a, --add-all-nodes Move on the tree both ways.
-o, --single-node-only Run only the given node.
-p, --print-all-nodes Print all available node options 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.
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