Nature Communications · 2022 · 45 citations · 41 references
Life SciencesBioinformaticsGeneticsComputational BiologyGenomicsMitochondrial GeneticsDna SequencingMitochondrial Genome VariationSingle-cell AnalysisSingle-cell GenomicsSingle-cell Rna Sequencing AnalysisSingle-cell Variant AnalysisClonal Population StructureMitochondrial Gene VariantsMitochondrial Variant AnalysisSingle-cell Dna SequencingSingle-cell Rna SequencingSingle-cell Variant CallingSubstructure FormationSubstructure Search
Mitochondrial mutations are increasingly recognised as informative endogenous genetic markers that can be used to reconstruct cellular clonal structure using single-cell RNA or DNA sequencing data. However, identifying informative mtDNA variants in noisy and sparse single-cell sequencing data is still challenging with few computation methods available. Here we present an open source computational tool MQuad that accurately calls clonally informative mtDNA variants in a population of single cells, and an analysis suite for complete clonality inference, based on single cell RNA, DNA or ATAC sequencing data. Through a variety of simulated and experimental single cell sequencing data, we showed that MQuad can identify mitochondrial variants with both high sensitivity and specificity, outperforming existing methods by a large extent. Furthermore, we demonstrate its wide applicability in different single cell sequencing protocols, particularly in complementing single-nucleotide and copy-number variations to extract finer clonal resolution.
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Comprehensive Integration of Single-Cell Data
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