Skip to main content

A simple MAFFT-based Multiple Sequence Alignment (MSA) library

Project description

ataserinyelMSA

A simple MAFFT-inspired Multiple Sequence Alignment (MSA) tool written in Python.

Installation

pip install ataserinyelMSA

Usage

python main.py input.fasta output.fasta

Example

Input (input.fasta):

>seq1
GATTACA
>seq2
GCATGCU
>seq3
AGCTAGC

Output (output.fasta):

>seq1
-GAT-TACA
>seq2
-GC-ATGCU
>seq3
AGCTA-GC-

Algorithm

This tool implements a simplified version of the MAFFT FFT-NS-1 algorithm:

  1. FASTA Parsing - Read and write FASTA format files
  2. Pairwise Alignment - Needleman-Wunsch global alignment algorithm
  3. Distance Matrix - Compute pairwise distances between sequences
  4. Guide Tree - UPGMA clustering algorithm
  5. Progressive Alignment - Align sequences following the guide tree order

Differences from original MAFFT

  • Uses Needleman-Wunsch instead of FFT for similarity calculation
  • Simple +1/-1 scoring matrix instead of advanced substitution matrices
  • Suitable for small datasets

Author

Ata Serinyel

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ataserinyelmsa-0.1.0.tar.gz (6.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ataserinyelmsa-0.1.0-py3-none-any.whl (6.8 kB view details)

Uploaded Python 3

File details

Details for the file ataserinyelmsa-0.1.0.tar.gz.

File metadata

  • Download URL: ataserinyelmsa-0.1.0.tar.gz
  • Upload date:
  • Size: 6.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.2

File hashes

Hashes for ataserinyelmsa-0.1.0.tar.gz
Algorithm Hash digest
SHA256 7275c2264710142f6e3cc236e94b2bbfefbb5db711e478c4cd551bb8bdb78a32
MD5 b33e6525a855fcb814b4308542bcbb70
BLAKE2b-256 3a261b01d5cf28629a72eea97ab0395c2734008d875bc66f9ea18f611549e378

See more details on using hashes here.

File details

Details for the file ataserinyelmsa-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: ataserinyelmsa-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 6.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.2

File hashes

Hashes for ataserinyelmsa-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 fad77969dcc39c3a3e8a21269c6f939d9543fda069ef5fc5ea04ee851e63e3c2
MD5 8bfdfec4afefd44749ca6c7d3c980604
BLAKE2b-256 e8224ead7b8e2d0a5ccfbc3aef336a6c7d0144b3744f19fce6966681d7e7a63f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page