https://github.com/moshi4/pybarrnap
Python implementation of barrnap (Bacterial ribosomal RNA predictor)
https://github.com/moshi4/pybarrnap
bioinformatics genome-annotation genomics microbial-genomics microbiology python rna
Last synced: 6 months ago
JSON representation
Python implementation of barrnap (Bacterial ribosomal RNA predictor)
- Host: GitHub
- URL: https://github.com/moshi4/pybarrnap
- Owner: moshi4
- License: gpl-3.0
- Created: 2024-01-24T10:12:44.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-03-13T15:25:01.000Z (over 1 year ago)
- Last Synced: 2024-04-14T07:11:59.965Z (over 1 year ago)
- Topics: bioinformatics, genome-annotation, genomics, microbial-genomics, microbiology, python, rna
- Language: Python
- Homepage:
- Size: 21.1 MB
- Stars: 7
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
# pybarrnap: Python implementation of barrnap
[](https://pypi.python.org/pypi/pybarrnap)
[](https://anaconda.org/bioconda/pybarrnap)
[](https://github.com/moshi4/pybarrnap/actions/workflows/ci.yml)
## Table of contents
- [Overview](#overview)
- [Installation](#installation)
- [CLI Usage](#cli-usage)
- [API Usage](#api-usage)
- [LICENSE](#license)
## Overview
pybarrnap is a python implementation of [barrnap](https://github.com/tseemann/barrnap) (Bacterial ribosomal RNA predictor).
pybarrnap provides a CLI compatible with barrnap and also provides a python API for running rRNA prediction and retrieving predicted rRNA.
pybarrnap default mode depends only on the python library and not on the external command-line tools nhmmer and bedtools.
As an additional feature from barrnap, accurate mode is available by installing the external command-line tool cmscan([infernal](http://eddylab.org/infernal/)).
> [!NOTE]
> Barrnap v0.9 uses the HMM profile database created from older releases of Rfam and SILVA.
> On the other hand, pybarrnap default mode uses the HMM profile database created from the Rfam(14.10).
> Therefore, there will be some differences in results between Barrnap v0.9 and pybarrnap default mode.
## Installation
`Python 3.8 or later` is required for installation.
pybarrnap depends on [pyhmmer](https://github.com/althonos/pyhmmer) and [biopython](https://github.com/biopython/biopython) python library.
If accurate mode is required, please install [infernal](http://eddylab.org/infernal/) additionally.
**Install PyPI package:**
pip install pybarrnap
**Install bioconda package:**
conda install -c conda-forge -c bioconda pybarrnap
**Use Docker ([Image Registry](https://github.com/moshi4/pybarrnap/pkgs/container/pybarrnap)):**
docker run -it --rm ghcr.io/moshi4/pybarrnap:latest pybarrnap -h
## CLI Usage
### Basic Command
pybarrnap genome.fna > genome_rrna.gff
### Options
$ pybarrnap --help
usage: pybarrnap [options] genome.fna[.gz] > genome_rrna.gff
Python implementation of barrnap (Bacterial ribosomal RNA predictor)
positional arguments:
fasta Input fasta file (or stdin)
optional arguments:
-e , --evalue E-value cutoff (default: 1e-06)
-l , --lencutoff Proportional length threshold to label as partial (default: 0.8)
-r , --reject Proportional length threshold to reject prediction (default: 0.25)
-t , --threads Number of threads (default: 1)
-k , --kingdom Target kingdom [bac|arc|euk|all] (default: 'bac')
kingdom='all' is available only when set with `--accurate` option
-o , --outseq Output rRNA hit seqs as fasta file (default: None)
-i, --incseq Include FASTA input sequences in GFF output (default: OFF)
-a, --accurate Use cmscan instead of pyhmmer.nhmmer (default: OFF)
-q, --quiet No print log on screen (default: OFF)
-v, --version Print version information
-h, --help Show this help message and exit
> [!TIP]
> If `--accurate` option is set, cmscan(infernal) is used for rRNA search instead of pyhmmer.nhmmer.
> Although cmscan is slower than pyhmmer.nhmmer, it is expected to give more accurate results because it performs rRNA searches using RNA secondary structure profiles.
### CLI Example
Click [here](https://github.com/moshi4/pybarrnap/raw/main/examples/examples.zip) to download examples dataset.
#### CLI Example 1
Print rRNA prediction result on screen
pybarrnap examples/bacteria.fna
#### CLI Example 2
Output rRNA predition result to file
pybarrnap examples/archaea.fna -k arc --outseq rrna.fna --incseq > rrna_incseq.gff
#### CLI Example 3
With pipe stdin
cat examples/fungus.fna | pybarrnap -q -k euk | grep 28S
## API Usage
pybarrnap provides simple API for running rRNA prediction and retrieving predicted rRNA.
[](https://colab.research.google.com/github/moshi4/pybarrnap/blob/main/notebooks/pybarrnap.ipynb)
```python
from pybarrnap import Barrnap
from pybarrnap.utils import load_example_fasta_file
# Get example fasta file path
fasta_file = load_example_fasta_file("bacteria.fna")
# Run pybarrnap rRNA prediction
barrnap = Barrnap(
fasta_file,
evalue=1e-6,
lencutoff=0.8,
reject=0.25,
threads=1,
kingdom="bac",
accurate=False,
quiet=False,
)
result = barrnap.run()
# Output rRNA GFF file
result.write_gff("bacteria_rrna.gff")
# Output rRNA GFF file (Include input fasta sequence)
result.write_gff("bacteria_rrna_incseq.gff", incseq=True)
# Output rRNA fasta file
result.write_fasta("bacteria_rrna.fna")
# Get rRNA GFF text and print
print("\n========== Print rRNA GFF ==========")
print(result.get_gff_text())
# Get rRNA features and print
print("\n========== Print rRNA features ==========")
for rec in result.seq_records:
for feature in rec.features:
print(feature.id, feature.type, feature.location, feature.qualifiers)
# Get rRNA sequences and print
print("\n========== Print rRNA sequences ==========")
for rec in result.get_rrna_seq_records():
print(f">{rec.id}\n{rec.seq}")
```
## LICENSE
pybarrnap was reimplemented in python based on the perl implementation of Barrnap v0.9.
HMM(Hidden Marcov Model) and CM(Covariance Model) profile database for pybarrnap was created from Rfam(14.10).
- pybarrnap: [GPLv3](https://github.com/moshi4/pybarrnap/blob/main/LICENSE)
- Barrnap([v0.9](https://github.com/tseemann/barrnap/tree/0.9)): [GPLv3](https://github.com/moshi4/pybarrnap/blob/main/src/pybarrnap/db/LICENSE.Barrnap)
- Rfam([14.10](https://ftp.ebi.ac.uk/pub/databases/Rfam/14.10/)): [CC0](https://github.com/moshi4/pybarrnap/blob/main/src/pybarrnap/db/LICENSE.Rfam)