Sequence analyzer (bioinformatics)

About

This is a set of simple command-line python scripts with 101 algorihtms used in bioinformatics.

Features

• Pariwise local alignment (Smith-Waterman algorithm)
• Pairwise global alignment (Needleman-Wunsch algorithm)
• Edit distance and similarity (Needleman-Wunsch algorithm)
• RNA to amino acids translation

Available commands

Usage: analyze.py [OPTIONS] SEQUENCE_A SEQUENCE_B

Options:
  -S, --summary
  -s, --similarity
  -e, --edit-distance
  -a, --alignment [global|local]
  --load-csv                      Load scores.csv and edit_cost.csv
  --help                          Show this message and exit.

Usage: translate.py [OPTIONS] [SEQUENCE]

Options:
  -i, --input-file FILE  Path to text file containing long nucleotide sequences (1 sequence = 1 line)
  --help                 Show this message and exit.

Usage examples

python analyze.py AGCT AGGT --summary
python analyze.py AGCT AGGT --similarity
python analyze.py AGCT AGGT --edit-distance
python analyze.py AGCT AGGT --edit-distance --load-csv
python analyze.py AGCT AGGT --alignment local
python analyze.py AGCT AGGT --alignment global

python translate.py AUGACGGAGCUUCGGAGCUAG
python translate.py --input-file rna.txt

Output examples:

python analyze.py ACCC ACCT -e

[[0 1 2 3 4]
 [1 0 1 2 3]
 [2 1 0 1 2]
 [3 2 1 0 1]
 [4 3 2 1 1]]
[['' 'A' 'C' 'C' 'T']
 ['A' '↖' '←' '←' '←']
 ['C' '↑' '↖' '↖' '←']
 ['C' '↑' '↖' '↖' '←']
 ['C' '↑' '↖' '↖' '↖']]
[Edit distance] Cost=1

python translate.py --input-file rna.txt

MNACFSNLCYESKSIGG
MSDTLSQRLRASLGAIRIAFNLGRSAELD

Requirements

• Python 3.7 (type annotations)
• numpy (storing matrices)
• pandas (loading CSV into DataFrame)
• click (CLI interface)

We recommend using conda/virtualenv/pyenv environment (this step is optional)

conda create --name sequence-analyzer-env python=3.7 pip

Requirements installation

pip install -r requirements.txt

Customization

Default scoring values:

# SequenceAnalyzer.py
self.scoring_sys = ScoringSystem(match=1, mismatch=-1, gap=-1)
self.edit_cost_sys = ScoringSystem(match=0, mismatch=1, gap=1)

You can set up your own similarity and edit cost matrices by adding --load-csv flag

(these files are read by default)

scores.csv

edit_cost.csv

(Note: if any of your sequences contains invalid symbols, default values from ScoringSystem will be used instead)

Credits

• Michał Martyniak (@micmarty)
• Artur Śliwa (@asliwa)

License

Feel free play around with our code. If you see any bugs, please tell us about them in issues ❤️!

Apache License 2.0