A fast tool to calculate Hamming distances

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Project description

A small C++ tool to calculate pairwise distances between gene sequences given in fasta format.

Python interface

To use the Python interface, you should install it from PyPI:

python -m pip install hammingdist

Then, you can e.g. use it in the following way from Python:

import hammingdist

# To see the different optional arguments available:
help(hammingdist.from_fasta)

# To import all sequences from a fasta file
data = hammingdist.from_fasta("example.fasta")

# To import only the first 100 sequences from a fasta file
data = hammingdist.from_fasta("example.fasta", n=100)

# To import all sequences and remove any duplicates
data = hammingdist.from_fasta("example.fasta", remove_duplicates=True)

# To import all sequences from a fasta file, also treating 'X' as a valid character
data = hammingdist.from_fasta("example.fasta", include_x=True)

# The distance data can be accessed point-wise, though looping over all distances might be quite inefficient
print(data[14,42])

# The data can be written to disk in csv format (default `distance` Ripser format) and retrieved:
data.dump("backup.csv")
retrieval = hammingdist.from_csv("backup.csv")

# It can also be written in lower triangular format (comma-delimited row-major, `lower-distance` Ripser format):
data.dump_lower_triangular("lt.txt")
retrieval = hammingdist.from_lower_triangular("lt.txt")

# If the `remove_duplicates` option was used, the sequence indices can also be written.
# For each input sequence, this prints the corresponding index in the output:
data.dump_sequence_indices("indices.txt")

# Finally, we can pass the data as a list of strings in Python:
data = hammingdist.from_stringlist(["ACGTACGT", "ACGTAGGT", "ATTTACGT"])

The Python package is currently built without OpenMP support, but this can be changed upon request.

Project details

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Release history Release notifications | RSS feed

1.3.0

Aug 20, 2024

1.2.0

Mar 4, 2024

1.1.0

Feb 19, 2024

1.0.0

Jan 10, 2024

0.21.0

Nov 13, 2023

0.20.0

Aug 10, 2023

0.19.0

Jan 30, 2023

0.18.0

Sep 5, 2022

0.17.0

Sep 5, 2022

0.16.0

Apr 13, 2022

0.15.0

Apr 11, 2022

0.13.0

Dec 3, 2021

0.12.0

Jul 19, 2021

This version

0.11.0

Jul 19, 2021

0.10.0

Jun 23, 2021

0.8

Nov 25, 2020

0.7

Nov 24, 2020

0.6

Nov 16, 2020

0.5

Nov 16, 2020

0.4

Nov 13, 2020

0.3

Oct 30, 2020

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