dnazip

• A Python implementation of The Burrows-Wheeler Transform (BWT) alongside Huffman compression on DNA sequences.
• Hosted on GitHub
• Documentation? here

Demo

• A demo for installation and using the GUI can be found here

Installation

• You can install the package either from pip or from the source code hosted on github.

With pip

pip install dnazip-bioinfo

From source

git clone https://github.com/dabane-ghassan/dnazip.git
cd dnazip
sudo python3 setup.py install

Getting started

GUI

• After installing the package from source or using pip, the interface can be launched simply from the command line:

dnazip

• If problems occur with the installation, an interface instance can be imported and launched:

from dnazip.interface import Interface
gui = Interface()
gui.main()

Using the library

Generating a random DNA sequence

• A random DNA sequence with an alphabet of ATCGN can be generated for any given length specified in the parameter.

from dnazip.sequence import Sequence
randseq = Sequence.generate(length=5000)
Sequence('/path/to/new/seq').write(randseq)

Encoding a DNA sequence with Burrows-Wheeler + Huffman Coding

• To encode a DNA sequence using BWT and Huffman coding, you can use a FullEncoder object that will save two files to the same directory as the sequence, the Burrows-Wheeler transform and the UTF-8 zipped format of the sequence:

from dnazip.encoder import FullEncoder
encode = FullEncoder('/path/to/seq')
encode.full_zip()

• The attributes of the object can be accessed to see intermediary results:

encode.bw_encoder.rotations # a matrix of string rotations from a sequence
encode.bw_encoder.bwm # The Burrows-Wheeler Matrix
encode.bw_encoder.bwt # The Burrows-Wheeler Transform

encode.huff_encoder.header # The header of the zip file that contains Huffman codes for each character as well as the sequence binary padding
encode.huff_encoder.binary # The binary sequence of the BW transform
encode.huff_encoder.unicode # 8-bits encoded binary sequence

• A random sequence of size 1kB was compressed efficiently to 549 bytes.

Decoding a DNA sequence with Huffman decoding + Reversing Burrows-Wheeler transform

• To decode a zipped DNA sequence using Huffman decoding and the inverse of BWT, you can use a FullDecoder object that will work in the same manner as the FullEncoder object:

from dnazip.decoder import FullDecoder
decode = FullDecoder('path/to/seq')
decode.full_unzip()

• The attributes can also be accessed to see intermediary results:

decode.huff_decoder.header # The header of the zip file that contains Huffman codes for each character as well as the sequence binary padding that where saved when the Huffman tree was created
decode.huff_decoder.unicode # 8-bits encoded sequence
decode.huff_decoder.binary # The binary sequence

decode.bw_decoder.bwm # The Burrows-Wheeler reconstructed matrix
decode.bw_decoder.original # The original sequence

Building the Burrows-Wheeler transform using the advanced algorithm

• The BWT can be constructed using a Suffix Array (SA) based algorithm that has a better time and space complexities:

from dnazip.sequence import Sequence
from dnazip.burros_wheeler import BurrosWheeler

seq = Sequence('/path/to/seq').read()
BurrosWheeler.bwt_advanced(seq)

Documentation

Detailed documentation on the architecture can be found here

About

📜 License

MIT Licensed © Ghassan Dabane, 2021.