MQuad

MQuad identifies mitochondrial DNA (mtDNA) variants from single-cell sequencing data to detect clonally informative mutations and quantify heteroplasmy for clonal analysis.

Key Features:

• Clonally Informative Variant Detection: Identifies mtDNA variants that serve as endogenous genetic markers to infer clonal architecture from single cells.
• Binomial Mixture Model: Applies a binomial mixture model to assess mtDNA heteroplasmy levels and distinguish biological signal from background noise.
• High Sensitivity and Specificity: Reported higher sensitivity and specificity on simulated and experimental datasets compared to existing methods.
• Comprehensive Analysis Suite: Provides tools for clonality inference and integration of mtDNA information with single-cell RNA or DNA sequencing protocols.
• Versatile Applicability: Compatible with various single-cell sequencing methods to enhance clonal analysis alongside other genomic variation data.

Scientific Applications:

• Cellular Heterogeneity and Evolution: Resolves intra-sample clonal structures by using mtDNA variants to track lineage relationships and population genetics.
• Cancer Biology: Identifies clonally informative mitochondrial mutations to map tumor subclones and investigate tumor evolution.
• Developmental Biology: Traces clonal dynamics during development by detecting heteroplasmic mtDNA variants across single cells.
• Disease Progression: Monitors clonal shifts and mitochondrial variant distributions associated with disease progression at single-cell resolution.

Methodology:

Uses a binomial mixture model on single-cell RNA or DNA sequencing–derived mtDNA read counts to assess heteroplasmy and separate true variants from background noise.