BCAWT
BCAWT: Automated tool for codon usage bias analysis for molecular evolution - Published in JOSS (2019)
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Published in Journal of Open Source Software
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Repository
BCAWT: Automated tool for codon usage bias analysis for molecular evolution
Basic Info
Statistics
- Stars: 5
- Watchers: 1
- Forks: 1
- Open Issues: 1
- Releases: 1
Metadata Files
README.md
BCAWT: Automated tool for codon usage bias analysis for molecular evolution
BCAW tool Updates
Now you can run BCAW tool using a GUI software that can work on any operating system. It is very easy to use. For more information and to download it: BCAWT-GUI.
Statement of Need
There are no tools available enable users to run a whole automated workflow for codon usage bias analysis. Using python 3.7 BCAW Tool ( Bio Codon Analysis Workflow Tool ) was developed to address this problem. BCAW Tool manages a complete automated workflow to analyze the codon usage bias for genes and genomes of any organism. With minimum coding skills.
For more details about codon usage bias , and the equations used in BCAWT see.
Dependencies
1- Biopython
2- pandas
3- cai2
4- scipy
5- matplotlib
6- numpy
7- prince
Installation Instructions
Using pip
python
pip install git+https://github.com/AliYoussef96/BCAW-Tool.git
Note: Python >=3.7 is required.
Contribution Guidelines
Contributions to the software are welcome
For bugs and suggestions, the most effective way is by raising an issue on the github issue tracker. Github allows you to classify your issues so that we know if it is a bug report, feature request or feedback to the authors.
If you wish to contribute some changes to the code then you should submit a pull request How to create a Pull Request? documentation on pull requests
Usage
Auto testing
Note here we try to test the result of BCAW tool and not the modules, for testing the modules in the package use test.py
First download fasta file containing the coding sequence ( you can download any fasta file containing gene sequences to be analyzed from NCBI database).
or just download that file Test file
then run ( It will automatically run a test on the results files ):
```python from BCAWT import BCAWTautotest path = "Testfolder" # absolute path to the directory to save the result in testfasta = "Testfastafile" # absolute path to the fasta file that will be tested BCAWTautotest.autotest(path, testfasta)
processing....
BCAWTautotest.autocheckfiles(path) # note: this test assumes that in the result folder nothing except the result files form the above function. ```
Main Usage
python
from BCAWT import BCAWT
BCAWT.BCAW(['Ecoli.fasta'],'save_path',genetic_code_=11,Auto=True)
Input
```
mainfastafile (list): list of string of the file's path or file-like object
save_path (str): absolute path to the directory to save the result in, default = the current directory
reffastafile (list): list of string of the file's path or file-like object, default = None
Auto (bool): default = False, if reffastafile not None.
geneticcode (int) : default = 1, The Genetic Codes number described by NCBI
``` Important Note: BCAW tool expect coding sequences as input and not genes, for more information about what the difference between them you can take a look here
To obtain such fasta file for a species of interest
Say that the species of interest is Escherichia coli str. K-12 substr. MG1655:
1- Go to the NCBI database.
2- In the search bar write ( Escherichia coli str. K-12 substr. MG1655, complete genome ).
3- choose one of the results ( depending on what you want in your analysis ).
3- On the right of the page, you will find send to option. From sent to select Coding Sequences then FASTA nucleotides Finally, press on Create File
For NCBI Genomes Download (FTP) FAQ
Output
The expected CSV files output
|CSV file name|Description| |------------|-----------| | ATCG | contains ; gene id, GC, GC1, GC2, GC3, GC12, AT, AT3 A3, T3, C3, G3, GRAVY, AROMO and, Gene Length | | CARSCU | contains ; each RSCU result for each codon in each genes | | CARSCUcodons | contains ; correspondence analysis first 4 axis for each codon | | CA_RSCUgenes | contains ; correspondence analysis first 4 axis for each gene | | CAI | contains ; gene id and CAI index | | ENc | contains ; gene id and ENc index. | | P2-index | contains ; gene id and P2 index | | optimal codons | contains; putative optimal codons detected |
All output plots from BCAW tool analysis for coding sequence from Escherichia coli
Documentations
- An intro to the codon usage bias >> CUB introduction
- For more information about the equations used to analyze CUB in the BCAW tool >> Equations
- For more information about the output >> Output
- For more information about the abbreviations used >> Abbreviations table
Citation
Anwar, (2019). BCAWT: Automated tool for codon usage bias analysis for molecular evolution. Journal of Open Source Software, 4(42), 1500, https://doi.org/10.21105/joss.01500
Owner
- Name: Ali Youssef
- Login: AliYoussef96
- Kind: user
- Location: Egypt
- Company: Cairo university
- Website: https://www.linkedin.com/in/ali-youssef-455a92130/
- Repositories: 3
- Profile: https://github.com/AliYoussef96
Trying to be a Bioinformatician
JOSS Publication
BCAWT: Automated tool for codon usage bias analysis for molecular evolution
Authors
Department of Genetics, Faculty of Agriculture, Cairo University, 12613, Cairo, Egypt
Editor
Melissa Gymrek
Tags
Codon Usage Analysis Automated Workflow Putative optimal codonsGitHub Events
Total
- Issues event: 1
- Issue comment event: 1
- Push event: 25
Last Year
- Issues event: 1
- Issue comment event: 1
- Push event: 25
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Ali Youssef | 4****6 | 402 |
| Benjamin Lee | b****e@c****u | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 14
- Total pull requests: 1
- Average time to close issues: 2 months
- Average time to close pull requests: 39 minutes
- Total issue authors: 4
- Total pull request authors: 1
- Average comments per issue: 1.79
- Average comments per pull request: 1.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- Benjamin-Lee (11)
- YDD99 (1)
- symonovar (1)
- Liiii007 (1)
Pull Request Authors
- Benjamin-Lee (1)
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Packages
- Total packages: 1
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Total downloads:
- pypi 34 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 6
- Total maintainers: 1
pypi.org: bcawt
Manages a complete workflow to analysis the codon usage bias
- Homepage: https://github.com/AliYoussef96/BCAW-Tool
- Documentation: https://bcawt.readthedocs.io/
- License: MIT
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Latest release: 1.0.6
published about 3 years ago
Rankings
Maintainers (1)
Dependencies
- CAI *
- biopython *
- matplotlib *
- numpy *
- pandas *
- prince *
- scipy *