https://github.com/linsalrob/genbank_to
Convert genbank files to a swath of other formats
https://github.com/linsalrob/genbank_to
Last synced: 11 months ago
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Convert genbank files to a swath of other formats
- Host: GitHub
- URL: https://github.com/linsalrob/genbank_to
- Owner: linsalrob
- License: mit
- Created: 2022-04-14T04:25:25.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2023-09-29T10:58:18.000Z (almost 3 years ago)
- Last Synced: 2024-04-26T06:21:32.107Z (about 2 years ago)
- Language: Python
- Size: 46.9 KB
- Stars: 11
- Watchers: 4
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
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README
# genbank_to
[](https://edwards.flinders.edu.au/)
[](https://www.zenodo.org/badge/latestdoi/481464683)
[](https://opensource.org/licenses/MIT)
[](https://pypi.org/project/genbank_to/)
A straightforward application to convert NCBI GenBank format files to a swath of other formats. Hopefully we have the
format you need, but if not either post [an issue](https://github.com/linsalrob/genbank_to/issues) using our template,
or if you have already got it working, post [a PR](https://github.com/linsalrob/genbank_to/pulls) so we can add it and
add you to the project.
You might also be interested [deprekate's](https://github.com/deprekate/) package called [genbank](https://github.com/deprekate/genbank) which includes
several of the features here, and you can `import genbank` into your Python projects.
# What it does
Read an NCBI GenBank format file (like our [test data](test/NC_001417.gbk)) and convert it to one of many
different formats.
# Input formats
At the moment we only support NCBI GenBank format. If you want us to read other common formats,
[let us know](https://github.com/linsalrob/genbank_to/issues) and we'll add them.
# Output formats
Here are the output formats you can request. You can request as many of these at once as you like!
These outputs are assuming you provide a (for example) genome file that contains ORFs, Proteins, and Genomes.
## Nucleotide output
- `-n` or `--nucleotide` outputs the whole DNA sequence (e.g. the genome)
- `-o` or `--orfs` outputs the DNA sequence of the open reading frames
## Protein output
- `-a` or `--aminoacids` outputs the protein sequence for each of the open reading frames
## Complex formats
- `-p` or `--ptt` NCBI ptt protein table. This is a somewhat deprecated NCBI format from their genomes downloads
- `-f` or `--functions` outputs tab separated data of `protein ID` and `protein function` (also called the `product`)
- `--gff3` outputs GFF3 format
- `--amr` outputs a GFF file, an amino acid fasta file, and a nucleotide fasta file as required by [AMR Finder Plus](https://github.com/ncbi/amr/wiki/Running-AMRFinderPlus#examples). Note that this format checks for validity that often crashes AMRFinderPlus
- `--phage_finder` outputs a unique format required by [phage_finder](http://phage-finder.sourceforge.net/)
## Output options
- `--pseudo` normally we skip pseudogenes (e.g. in creating amino acid fasta files). This will try and include pseudogenes, but often biopython complains and ignores them!
- `-i` or `--seqid` only output this sequence, or these sequences if you specify more than one `-i`/`--seqid`
- `-z` or `--zip` compress some of the outputs
- `--log` write logs to a different file
## Separate multi-GenBank files
If your GenBank files contains multiple sequence records (separated with `//`), you can provide the `--separate` flag.
This will write each entry into its own file. This is compatible with `-n`/`--nucleotide`, `-o`/`--orfs`, and
`-a`/`--aminoacids`. However, if you provide the `--separate` flag on its own, it will write each entry in your
multi-GenBank file to its own GenBank file.
## Examples
All of these examples use our [test data](test/NC_001417.gbk)
1. Extract a `fasta` of the genome:
```bash
genbank_to -g test/NC_001417.gbk -n test/NC_001417.fna
```
2. Extract the DNA sequences of the ORFs to a single file
```bash
genbank_to -g test/NC_001417.gbk -o test/NC_001417.orfs
```
3. Extract the protein (amino acid) sequences of the ORFs to a file
```bash
genbank_to -g test/NC_001417.gbk -a test/NC_001417.faa
```
4. Do all of these at once
```bash
genbank_to -g test/NC_001417.gbk -n test/NC_001417.fna -o test/NC_001417.orfs -a test/NC_001417.faa
```
# Installation
You can install `genbank_to` in three different ways:
1. Using conda
This is the easiest and recommended method.
```bash
mamba create -n genbank_to genbank_to
conda activate genbank_to
genbank_to --help
```
2. Using pip
I recommend putting this into a virtual environment:
```bash
virtualenv venv
source venv/bin/activate
pip install genbank_to
genbank_to --help
```
3. Directly from this repository
(Not really recommended as things might break)
```bash
git clone https://github.com/linsalrob/genbank_to.git
cd genbank_to
virtualenv venv
source venv/bin/activate
python setup.py install
genbank_to --help
```