https://github.com/linsalrob/genetic_codes
Python code for translating sequences using different NCBI translation tables and genetic codes.
https://github.com/linsalrob/genetic_codes
Last synced: about 1 year ago
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Python code for translating sequences using different NCBI translation tables and genetic codes.
- Host: GitHub
- URL: https://github.com/linsalrob/genetic_codes
- Owner: linsalrob
- License: mit
- Created: 2023-12-21T00:29:37.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-26T06:21:28.000Z (about 2 years ago)
- Last Synced: 2024-04-26T07:31:32.641Z (about 2 years ago)
- Language: C
- Homepage:
- Size: 1.46 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-virome - pygenetic_code - C and Python tools for genetic code translation. [conda, pip] [Python] (Sequence Analysis / Sequence Translation)
README
[](https://edwards.flinders.edu.au)
[](https://www.zenodo.org/badge/latestdoi/60999054)
[](https://opensource.org/licenses/MIT)
[](https://pypi.org/project/pygenetic-code/)
[](http://bioconda.github.io/recipes/pygenetic_code/README.html)
# Genetic Codes
A Python and C library with no external dependencies for translating DNA sequences into protein sequences using different translation tables (aka genetic codes).
The [NCBI Genetic Codes](https://www.ncbi.nlm.nih.gov/Taxonomy/Utils/wprintgc.cgi?chapter=tgencodes#SG1) are central to working with alternate genetic codes. This Python tool kit includes a library that exposes the genetic codes so you can query a codon and get its variants or query a code and get its table. We also provide fast mechanisms to translate DNA sequences into protein sequences using the translation table of your choice.
# Current genetic codes:
1. The Standard Code (transl_table=1). By default all transl_table in GenBank flatfiles are equal to id 1, and this is not shown. When transl_table is not equal to id 1, it is shown as a qualifier on the CDS feature.
2. The Vertebrate Mitochondrial Code (transl_table=2)
3. The Yeast Mitochondrial Code (transl_table=3)
4. The Mold, Protozoan, and Coelenterate Mitochondrial Code and the Mycoplasma/Spiroplasma Code (transl_table=4)
5. The Invertebrate Mitochondrial Code (transl_table=5)
6. The Ciliate, Dasycladacean and Hexamita Nuclear Code (transl_table=6)
9. The Echinoderm and Flatworm Mitochondrial Code (transl_table=9)
10. The Euplotid Nuclear Code (transl_table=10)
11. The Bacterial, Archaeal and Plant Plastid Code (transl_table=11)
12. The Alternative Yeast Nuclear Code (transl_table=12)
13. The Ascidian Mitochondrial Code (transl_table=13)
14. The Alternative Flatworm Mitochondrial Code (transl_table=14)
15. Blepharisma Nuclear Code (transl_table=15)
16. Chlorophycean Mitochondrial Code (transl_table=16)
21. Trematode Mitochondrial Code (transl_table=21)
22. Scenedesmus obliquus Mitochondrial Code (transl_table=22)
23. Thraustochytrium Mitochondrial Code (transl_table=23)
It is the similar to the bacterial code (transl_table 11) but it contains an additional stop codon (TTA) and also has a different set of start codons.
24. Rhabdopleuridae Mitochondrial Code (transl_table=24)
25. Candidate Division SR1 and Gracilibacteria Code (transl_table=25)
26. Pachysolen tannophilus Nuclear Code (transl_table=26)
27. Karyorelict Nuclear Code (transl_table=27)
28. Condylostoma Nuclear Code (transl_table=28)
29. Mesodinium Nuclear Code (transl_table=29)
30. Peritrich Nuclear Code (transl_table=30)
31. Blastocrithidia Nuclear Code (transl_table=31)
33. Cephalodiscidae Mitochondrial UAA-Tyr Code (transl_table=33)
# Installation
We recommend installing `pygenetic_code` with bioconda:
```bash
mamba create -n pygenetic_code -c bioconda pygenetic_code
pygenetic_code --version
```
Alternatively, you can install `pygenetic_code` with pip.
```python
pip install pygenetic_code
pygenetic_code --version
```
# Usage
There is a command line application, Python example code, and a library that you can use. The command line application and examples show you how to use the library.
## Example code
These examples show you how to incorporate `pygenetic_code` into your own Python code.
We have a very simple translate function that you can use if you want to translate one (or more) ORFs. The signature is
```python
translate(dna_sequence, translation_table)
```
and we have a simple example that translates a sequence:
```bash
python examples/translate_a_sequence.py
```
We can also translate DNA sequences in all six reading frames, and here is an example that reads a fasta file and translates all six frames using the bacterial genetic code (translation table 11):
```bash
python examples/translate_sequence_in_all_frames.py -f tests/JQ995537.fna -t 11
```
or an alternate genetic code (translation table 15):
```bash
python examples/translate_sequence_in_all_frames.py -f tests/JQ995537.fna -t 15
```
Or you can translate the _E. coli_ K-12 sequence, and so you can identify all the ORFs in that genome:
```bash
python examples/translate_sequence_in_all_frames.py -f tests/U00096.3.fna.gz -t 11
```
(yes, you can use gzip files without decompressing them).
This will take about 0.1 seconds to do the actual translation, but starting python and all the other overheads make it almost 3/4 second to run.
You can also look at the effect of translation tables on the same sequences by running
```bash
python examples/average_translation_length.py -f tests/JQ995537.fna # for crassphage
python examples/average_translation_length.py -f tests/U00096.3.fna.gz # for E. coli K-12
```
We recommend using our easy Python wrappers to access the translate functions
```python
from pygenetic_code import translate, six_frame_translation
```
But you can also access our C library directly, using the `PyGeneticCode` module (see below)
## Command line applications
`pygenetic_code` translates DNA sequences either in one reading frame or in all six reading frames using the translation table of your choice.
To translate a sequence in the current reading frame, you can use
```python
pygenetic_code --translate
```
First, make sure you have a DNA sequence. We provide a few in [tests/](tests/) including [a very short sequence](tests/seq.fasta), [crAssphage](tests/JQ995537.fna), and [E. coli])(tests/U00096.3.fna.gz).
## Library
### Using the C library directly in Python
You can import the C library by importing PyGeneticCode.
There are two main methods that you can call:
The first function just returns the translation of your DNA sequence in 5' -> 3' format, so for example, this is the method you might use to translate an ORF.
```python
PyGeneticCode.translate(DNA_sequence, translation_table)
```
(See [examples/translate_a_sequence.py](examples/translate_a_sequence.py_) for an example.
The second method returns all the 6 frame translations.
```python
PyGeneticCode.translate_six_frames(DNA_sequence, translation_table, verbose)
```
(See [examples/translate_sequence_in_all_frames.py](examples/translate_sequence_in_all_frames.py) for an example invocation.)
The DNA sequence is the DNA sequence you want to translate. The translation table must be one of the valid translation tables (see [pygenetic_code/genetic_code.translation_tables](pygenetic_code/genetic_code.translation_tables) for the valid tables).
## Translate a codon
Another way to access the code in your python application is to access the `translate_codon()` function, that has this signature:
```python
amino_acid = translate_codon(codon, translation_table=1, one_letter=False)
```
The `codon` is the codon that you want to translate as either an RNA (e.g. `AUG`) or DNA (e.g. `ATG`) sequence. The `translation_table` is your required translation table (see the [NCBI website](https://www.ncbi.nlm.nih.gov/Taxonomy/Utils/wprintgc.cgi?chapter=tgencodes#SG1) for valid tables), and `one_letter` is whether to return a three letter amino acid code (e.g. `Met` or `Ter`) or a one letter amino acid code (e.g. `M` or `*`).
The library provides other ways to access the genetic codes, and those are exemplified in the `pytest` files in [tests/](tests)
## Viewing translation tables
You can print the translation tables using the `pygenetic_code` command. There are currently a couple of options:
- `json` prints the table in machine readable json format.
- `difference` prints a `.tsv` file with the the difference from the standard (translation table 1) code
- `maxdifference` prints a `.tsv` file with the difference from the most common amino acid. The main difference is that `TGA` is more frequently tryptophan than a stop.
-
# Citing
Please cite this repository as:
Edwards, Robert A. 2023. pygenetic_code. https://github.com/linsalrob/genetic_codes. DOI: 10.5281/zenodo.10453453