easyalign

Python Implementation of classic local and global alignment algorithms

https://github.com/jamesdconley/easyalign

Science Score: 10.0%

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  • Academic publication links
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    Low similarity (5.5%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

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

Data Scientist at SFL Scientific (Personal Account)

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Last synced: over 2 years ago

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James Conley j****1@c****u 7
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Last synced: about 1 year ago

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Packages

  • Total packages: 1
  • 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

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 11 Last month
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 *