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Updated: Apr 19, 2026

Genotyping Single Nucleotide Polymorphisms in the Mitochondrial Genome by Pyrosequencing
Published on: February 10, 2023
Phy-Mer: a novel alignment-free and reference-independent mitochondrial haplogroup classifier
Daniel Navarro-Gomez1, Jeremy Leipzig1, Lishuang Shen1
1Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, MA, USA, Center for Biomedical Informaticsand Center for Mitochondrial and Epigenomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA, Department of Clinical Genetics, Maastricht University Medical Centre, The Netherlands, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA, Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA and Department of Forensic Molecular Biology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Motivation:
All current mitochondrial haplogroup classification tools require variants to be detected from an alignment with the reference sequence and to be properly named according to the canonical nomenclature standards for describing mitochondrial variants, before they can be compared with the haplogroup determining polymorphisms. With the emergence of high-throughput sequencing technologies and hence greater availability of mitochondrial genome sequences, there is a strong need for an automated haplogroup classification tool that is alignment-free and agnostic to reference sequence.
Results:
We have developed a novel mitochondrial genome haplogroup-defining algorithm using a k-mer approach namely Phy-Mer. Phy-Mer performs equally well as the leading haplogroup classifier, HaploGrep, while avoiding the errors that may occur when preparing variants to required formats and notations. We have further expanded Phy-Mer functionality such that next-generation sequencing data can be used directly as input.
Availability And Implementation:
Phy-Mer is publicly available under the GNU Affero General Public License v3.0 on GitHub (https://github.com/danielnavarrogomez/phy-mer).
Contact:
Xiaowu_Gai@meei.harvard.edu
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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