Python bindings for QuickEd
Project description
QuickEd

QuickEd is a high-performance exact sequence alignment library based on the bound-and-align paradigm. Currently, QuickEd focuses on DNA sequence alignment (A, C, G, T, N), using the edit distance (Levenshtein distance) metric.
from quicked import QuickedAligner, QuickedException
pattern = "ACGT" # Pattern sequence
text = "ACTT" # Text sequence
score = -1 # Alignment score
cigar = "" # CIGAR string
try:
aligner = QuickedAligner() # Aligner object, with sensible default parameters
# Without any extra configuration, the aligner will use the Quicked algorithm
aligner.align(pattern, text) # Align the sequences!
score = aligner.getScore() # Get the score
cigar = aligner.getCigar() # Get the CIGAR string
except QuickedException as e:
print(e)
print(f"Score: {score}") # Print the score
print(f"Cigar: {cigar}") # Print the CIGAR string
QuickEd is actually a C library, and this package is it’s wrapper for Python. Check out QuickEd's GitHub for more code examples and more details on how QuickEd works.
Features
- Calculates edit distance (Levenshtein distance).
- It can find optimal alignment path (instructions on how to transform the first sequence into the second sequence).
- Supports multiple alignment algorithms:
- QuickEd
- BandEd
- WindowEd
- Efficient implementation of the bound-and-align paradigm.
- It scales to long and noisy sequences, even when finding an alignment path, while consuming very little memory thanks to the Hirschberg algorithm.
IMPORTANT! As QuickEd focuses on DNA sequence alignment, expected alphabet characters are limited to A, C, G, T, and N. However, no check is performed on the input sequences for performance reasons.
Installation
PyPI
QuickEd is available on PyPI, so you can install it using pip:
pip install quicked
Conda
Conda support is still in progress.
From source
To install the Python bindings from source, you can simply run pip install . from the root directory of the QuickEd repository. This will build and install the bindings for your current Python environment.
API
Take a look at basic.py for a minimal example.
QuickedAlgo
Enum that defines the alignment algorithm to use. The available algorithms are:
QUICKED: QuickEd algorithm (default)BANDED: BandEd algorithmWINDOWED: WindowEd algorithmHIRSCHBERG: Hirschberg algorithm
QuickedAligner
This class defines an aligner object that can be used to perform sequence alignment. It is initialized with default parameters and can be configured using various setter methods.
aligner = QuickedAligner()
align(pattern, text)
Aligns the provided pattern and text according to the current parameters.
- Parameters:
pattern(str): The pattern to be aligned.text(str): The text to be aligned against.
setAlgorithm(algorithm)
Sets the algorithm to be used for alignment.
- Parameters:
algorithm(QuickedAlgo): The alignment algorithm to use.
setOnlyScore(only_score)
Sets whether only the score should be computed.
- Parameters:
only_score(bool): A boolean indicating if only the score should be computed.
setBandwidth(bandwidth)
Sets the bandwidth for BandEd alignment.
- Parameters:
bandwidth(int): The bandwidth value to set.
setWindowSize(window_size)
Sets the window size for WindowEd alignment.
- Parameters:
window_size(int): The window size value to set.
setOverlapSize(overlap_size)
Sets the overlap size for WindowEd alignment.
- Parameters:
overlap_size(int): The overlap size value to set.
setForceScalar(force_scalar)
Forces scalar computation (i.e., no SIMD instructions).
- Parameters:
force_scalar(bool): A boolean indicating whether to force scalar computation.
setHEWThreshold(hew_threshold)
Sets the HEW threshold.
- Parameters:
hew_threshold(float): The HEW threshold value to set.
setHEWPercentage(hew_percentage)
Sets the HEW percentage.
- Parameters:
hew_percentage(float): The HEW percentage value to set.
getScore()
Gets the alignment score.
- Returns:
- (float): The alignment score as a numeric value.
getCigar()
Gets the CIGAR string representing the alignment.
- Returns:
- (str): A string representing the alignment in CIGAR format.
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