Haplotype-resolved de novo assembly of highly diverse virus genomes is critical in prevention, control and treatment of viral diseases. Current methods either can handle only relatively accurate short read data, or collapse haplotype-specific variations into consensus sequence. Here, we present Strainline, a novel approach to assemble viral haplotypes from noisy long reads without a reference genome. Strainline is the first approach to provide strain-resolved, full-length de novo assemblies of viral quasispecies from noisy third-generation sequencing data. Benchmarking on simulated and real datasets of varying complexity and diversity confirm this novelty and demonstrate the superiority of Strainline.

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Genome Biology
Algorithms for PAngenome Computational Analysis , Pan-genome Graph Algorithms and Data Integration

Luo, V., Kang, X., & Schönhuth, A. (2022). Strainline: Full-length de novo viral haplotype reconstruction from noisy long reads. Genome Biology, 23(1), 29:1–29:27. doi:10.1186/s13059-021-02587-6