Phylovar

Phylovar performs phylogeny-guided single-nucleotide variant (SNV) calling on single-cell sequencing data to improve SNV detection accuracy and enable scalable analysis of large scWGS and scWES datasets.

Key Features:

• Phylogeny-Guided Variant Calling: Utilizes evolutionary relationships among cells to improve accuracy in variant detection and mitigate technical errors inherent in single-cell whole-genome (scWGS) and whole-exome sequencing (scWES).
• Scalability: Processes large-scale sequencing datasets containing millions of loci, addressing scaling limitations reported for tools such as SCIΦ and scVILP.
• Performance: Benchmarking on simulated datasets indicates higher computational efficiency than SCIΦ and higher SNV detection accuracy than Monovar, a non-phylogeny-aware method.

Scientific Applications:

• Triple-Negative Breast Cancer Study: Applied to an scWES dataset of 32 cells and 3,375 loci to identify somatic SNVs with high or moderate functional impact that were corroborated by bulk sequencing data.
• Neuron Cell Analysis: Applied to an scWGS dataset of 16 neurons (~2.5 million loci) to detect 5,745 non-synonymous SNVs, with some variants linked to neurodegenerative diseases.

Methodology:

Phylovar employs a phylogeny-guided variant-calling approach that leverages evolutionary relationships among cells to enhance detection accuracy and address high error rates and limited coverage in single-cell sequencing data.