bioRxivBioinformaticsPreprint
Probabilistic cell lineage inference from mitochondrial mutations
Sophie SeideliD, Joanna HårdiD, Pedro FerreiraiD, Pietro BerkesiD, Katharina JahniD, Carl‐Johan ErikssoniD, Jeff Eron MoldiD, Jakob MichaëlssoniD, Jack KuipersiD, Niko BeerenwinkeliD
Abstract
Tracing genealogical relationships between cells and their molecular states is essential for understanding tissue development, maintenance and disease. We present mt-SCITE, a computational method that reconstructs cell division histories from mitochondrial mutations in single cells. On simulated and experimental benchmarks, mt-SCITE outperformed existing methods in terms of cell lineage reconstruction, and scaled to thousands of cells. Applied to expanded CD8+ T cells following vaccination, mt-SCITE resolved subclonal relationships and revealed clones with predominantly memory-like, effector-like, or mixed states. mt-SCITE robustly identifies clonally related populations and resolves substructure within them, providing a broadly applicable approach to study cell lineage development.
- organism: human
- assay: scRNA-seq
- research focus: clustering
- research focus: cell type annotation
- research focus: trajectory inference
- approach: statistical model
- Citations
- 1
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