PyFastANI
Zenodo (CERN European Organization for Nuclear Research)
Abstract
The average nucleotide identity (ANI) metric has become the gold standard for prokaryotic species delineation in the genomics era. The most popular ANI algorithms are available as command-line tools and/or web applications, making it inconvenient or impossible to incorporate them into bioinformatic workflows, which utilize the popular Python programming language. Here, we present PyOrthoANI, PyFastANI, and Pyskani, Python libraries for three popular ANI computation methods. ANI values produced by PyOrthoANI, PyFastANI, and Pyskani are virtually identical to those produced by OrthoANI, FastANI, and skani, respectively. All three libraries integrate seamlessly with BioPython, making it easy and convenient to use, compare, and benchmark popular ANI algorithms within Python-based workflows.
Authors 3
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Martin F. Larralde Aachen
Leiden University Medical Center
Affiliation as printed
Leiden University Medical Center
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Georg Zeller Aachen
Leiden University Medical Center
Affiliation as printed
Leiden University Medical Center
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Affiliation as printed
Umeå University