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 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.
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 Please cite if you find our tool useful.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file MirMachine-0.2.13.tar.gz
.
File metadata
- Download URL: MirMachine-0.2.13.tar.gz
- Upload date:
- Size: 12.5 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0a2d7d466a391b07a358ee543c34814974f8273cd42ce37f5ccb757169649411 |
|
MD5 | f30c17c7cf9444053f6d31a22b4c6034 |
|
BLAKE2b-256 | b0a2f956459566fa4cd61a05510567bb148a1c47a2f7a51b5df53149767be960 |