Mitoclone2: an R package for elucidating clonal structure in single-cell RNA-sequencing data using mitochondrial variants

Benjamin Story; Lars Velten; Gregor Mönke; Ahrmad Annan; Lars Steinmetz

doi:10.1093/nargab/lqae095

Mitoclone2: an R package for elucidating clonal structure in single-cell RNA-sequencing data using mitochondrial variants

NAR Genom Bioinform. 2024 Aug 9;6(3):lqae095. doi: 10.1093/nargab/lqae095. eCollection 2024 Sep.

Authors

Benjamin Story^{1

2}, Lars Velten³, Gregor Mönke⁴, Ahrmad Annan⁵, Lars Steinmetz^{1

6

7}

Affiliations

¹ Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
² Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
³ Center for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
⁴ Developmental Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
⁵ Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
⁶ Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
⁷ Stanford Genome Technology Center, Palo Alto, CA, USA.

Abstract

Clonal cell population dynamics play a critical role in both disease and development. Due to high mitochondrial mutation rates under both healthy and diseased conditions, mitochondrial genomic variability is a particularly useful resource in facilitating the identification of clonal population structure. Here we present mitoClone2, an all-inclusive R package allowing for the identification of clonal populations through integration of mitochondrial heteroplasmic variants discovered from single-cell sequencing experiments. Our package streamlines the investigation of this phenomenon by providing: built-in compatibility with commonly used tools for the delineation of clonal structure, the ability to directly use multiplexed BAM files as input, annotations for both human and mouse mitochondrial genomes, and helper functions for calling, filtering, clustering, and visualizing variants.