PyOrthoANI, PyFastANI, and Pyskani: a suite of Python libraries for computation of average nucleotide identity

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Summary: 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. Availability and Implementation: Source code is open-source and available via GitHub (PyOrthoANI, https://github.com/althonos/orthoani; PyFastANI, https://github.com/althonos/pyfastani; Pyskani, https://github.com/althonos/pyskani). Supplementary Information: Supplementary data are available on bioRxiv.

Authors 3

1. Martin F. Larralde

   European Molecular Biology Laboratory

   Affiliation as printed

   Structural and Computational Biology Unit, EMBL, 69117 Heidelberg, Germany;

2. Georg Zeller Aachen

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, 2333ZA Leiden, Netherlands;

3. Laura M. Carroll corresponding

   Umeå University · Science for Life Laboratory

   Affiliation as printed

   Department of Clinical Microbiology, SciLifeLab, Umea University, 90187 Umea, Sweden