https://github.com/alondmnt/codon-bias

Python package of codon usage bias analysis tools

https://github.com/alondmnt/codon-bias

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (8.7%) to scientific vocabulary

Keywords

bioinformatics codon-bias codon-models codon-usage codons computational-biology python
Last synced: 5 months ago · JSON representation

Repository

Python package of codon usage bias analysis tools

Basic Info
Statistics
  • Stars: 17
  • Watchers: 1
  • Forks: 8
  • Open Issues: 0
  • Releases: 5
Topics
bioinformatics codon-bias codon-models codon-usage codons computational-biology python
Created over 3 years ago · Last pushed 11 months ago
Metadata Files
Readme License

README.md

codon-bias

This package provides codon usage bias (CUB) analysis tools for genomic sequences, focusing on protein coding regions, translation efficiency and synonymous mutations. These include implementations of popular models from the past four decades of codon usage study, such as:

This package also includes tools for sequence optimization based on these codon usage models, and generators of random sequence permutations that can be used to compute empirical p-values and z-scores.

installation

pip install codon-bias

documentation

Read on Read the Docs.

cite

Diament, A. (2022). codon-bias (python package). https://doi.org/10.5281/zenodo.8039451

contributing

Contributions of additional models to the package are welcome! Please familiarize yourself with the existing classes, and try to conform to their style.

Owner

  • Name: Alon Diament Carmel
  • Login: alondmnt
  • Kind: user
  • Company: @PhenoAI

computational biologist & data scientist, PhD

GitHub Events

Total
  • Create event: 3
  • Issues event: 2
  • Release event: 3
  • Watch event: 9
  • Issue comment event: 18
  • Push event: 16
  • Pull request event: 3
  • Pull request review event: 3
  • Fork event: 3
Last Year
  • Create event: 3
  • Issues event: 2
  • Release event: 3
  • Watch event: 9
  • Issue comment event: 18
  • Push event: 16
  • Pull request event: 3
  • Pull request review event: 3
  • Fork event: 3

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 85
  • Total Committers: 1
  • Avg Commits per committer: 85.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Alon Diament a****t@u****m 85

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 3
  • Total pull requests: 3
  • Average time to close issues: 3 days
  • Average time to close pull requests: 12 days
  • Total issue authors: 3
  • Total pull request authors: 2
  • Average comments per issue: 1.0
  • Average comments per pull request: 2.33
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 3
  • Average time to close issues: about 20 hours
  • Average time to close pull requests: 12 days
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 0.0
  • Average comments per pull request: 2.33
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • zihian (1)
  • deyuanyang (1)
  • ShlozLavie (1)
Pull Request Authors
  • l-benedetti-insta (2)
  • moritzburghardt (2)
Top Labels
Issue Labels
question (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 2,530 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 8
  • Total maintainers: 1
pypi.org: codon-bias

codon usage bias analysis tools

  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 2,530 Last month
Rankings
Dependent packages count: 6.6%
Average: 25.9%
Downloads: 29.7%
Forks count: 30.5%
Dependent repos count: 30.6%
Stargazers count: 32.3%
Maintainers (1)
Last synced: 5 months ago

Dependencies

setup.py pypi
  • numpy *
  • pandas *
  • scipy *