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 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.

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 --model proto

See our documentation for detailed explanations: https://mirmachine.readthedocs.io/

Options and Arguments

MirMachine 0.3.0.5

Usage:
    MirMachine.py --node <text> --species <text> --genome <text> [--model <text>] [--evalue <float>] [--min-length <integer>] [--cpu <integer>] [--add-all-nodes|--single-node-only] [--unlock|--remove] [--touch] [--dry] [--long]
    MirMachine.py --species <text> --genome <text> --family <text> [--model <text>] [--evalue <float>] [--min-length <integer>] [--cpu <integer>] [--unlock|--remove] [--touch] [--dry] [--long]
    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 microRNA family (e.g. Let-7).
    -e <text>, --evalue <float>           Inclusion E-value. May inflate low quality hits. [default: 0.2] Default 5 if --long is used.
    --min-length <integer>                 Minimum precursor length in nucleotides. [default: 50]
    -c <integer>, --cpu <integer>         CPUs. [default: 2]

Options:
    -a, --add-all-nodes                 Move on the tree both ways. NOT required most of the time.
    -o, --single-node-only              Run only on the given node for microRNA families.
    --long                              Use long microRNA covariance models rather than standard models (Experimental).
    -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.
    --touch                             Touch output files (mark them up to date without really changing them).
    --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 microRNA families.
filtered_gff/ High confidence microRNA 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

Supplementary files repo: https://github.com/sinanugur/MirMachine-supplementary

Citation

Our Cell Genomics paper is here: https://doi.org/10.1016/j.xgen.2023.100348 Please cite if you find our tool useful.

MirMachine website: https://mirmachine.org