easyalign
Python Implementation of classic local and global alignment algorithms
Science Score: 10.0%
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1 of 1 committers (100.0%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (5.5%) to scientific vocabulary
Last synced: 10 months ago
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Repository
Python Implementation of classic local and global alignment algorithms
Basic Info
- Host: GitHub
- Owner: JamesDConley
- License: mit
- Language: Python
- Default Branch: master
- Size: 5.86 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 7 years ago
· Last pushed almost 6 years ago
https://github.com/JamesDConley/EasyAlign/blob/master/
# EasyAlign This software can align python lists of any objects that can be compared with the '==' operator (strings, floats, whatever!) ## Getting started The easiest way to install is with pip! `pip install EasyAlign` ## Usage ``` from EasyAlign import LocalAligner, GlobalAligner seq1 = [5, 1, 2, 3, 4, 5] seq2 = [5, 1, 1, 1, 1, 1, 2, 3] my_local_aligner = LocalAligner(2, -1) aligned_seq1, aligned_seq2, score = my_local_aligner.align(seq1, seq2) print(aligned_seq1, aligned_seq2, score ) my_global_aligner = GlobalAligner(2, -1) aligned_seq1, aligned_seq2, score = my_global_aligner.align(seq1, seq2) print(aligned_seq1, aligned_seq2, score ) ``` If you want to look at more local alignments than just the best scored one you can directly access the score table from the last alignment using my_local_aligner.table - it's a 2d list of integers. You can then pass the x,y coordinates (seq1 is x, seq2 is y) to my_local_aligner.traceback(x,y) which will return the aligned local sequences that end at that x/y coord. ## Thank You! Thanks for using EasyAlign! :)
Owner
- Name: James Conley
- Login: JamesDConley
- Kind: user
- Repositories: 3
- Profile: https://github.com/JamesDConley
Data Scientist at SFL Scientific (Personal Account)
GitHub Events
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Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| James Conley | j****1@c****u | 7 |
Committer Domains (Top 20 + Academic)
conncoll.edu: 1
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total 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
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
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Packages
- Total packages: 1
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Total downloads:
- pypi 11 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 1
- Total maintainers: 1
pypi.org: easyalign
Simple Python Implementation of the Smith-Waterman and Needleman-Wunsch Algorithms
- Homepage: https://github.com/JamesDConley/EasyAlign
- Documentation: https://easyalign.readthedocs.io/
- License: MIT
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Latest release: 0.1
published over 7 years ago
Rankings
Dependent packages count: 10.0%
Dependent repos count: 21.7%
Forks count: 29.8%
Average: 30.0%
Stargazers count: 38.8%
Downloads: 49.5%
Maintainers (1)
Last synced:
10 months ago
Dependencies
setup.py
pypi
- beautifulsoup4 *
- get *
- validators *