MitoDelta

MitoDelta detects mitochondrial DNA (mtDNA) deletions at cell-type resolution from single-cell RNA sequencing data.

Key Features:

• Sensitive alignment strategy: MitoDelta employs a sensitive alignment approach to identify deletion events from single-cell transcriptomes.
• Statistical filtering: MitoDelta applies robust statistical filtering based on a beta-binomial model to accurately identify deletion events from noisy single-cell transcriptomes.
• Cell-type pooling: MitoDelta analyzes reads pooled by annotated cell types to capture cell-type-specific deletion patterns.
• Deletion burden quantification: MitoDelta quantifies deletion burden across distinct cellular populations.

Scientific Applications:

• Disease-associated mtDNA deletion detection: MitoDelta enables detection of mtDNA deletion variants associated with mitochondrial disorders and neurodegenerative diseases.
• Cell-type-specific mutational landscape analysis: MitoDelta resolves mtDNA deletions at single-cell resolution to reveal cell-type-specific mutational landscapes masked by bulk methods.
• Neuronal subtype analysis in Parkinson's disease: MitoDelta reveals distinct mtDNA deletion burdens across neuronal subtypes in single-nucleus RNA sequencing datasets for Parkinson's disease.
• Public dataset reanalysis: MitoDelta provides a framework for reanalyzing public single-cell RNA sequencing datasets to study mitochondrial genome alterations at cell-type resolution.

Methodology:

MitoDelta combines a sensitive alignment strategy with robust statistical filtering based on a beta-binomial model, and analyzes reads pooled by annotated cell types.