ViSpA

ViSpA reconstructs viral quasispecies spectra from high-throughput sequencing data to characterize intra-host diversity of RNA viruses.

Key Features:

• Quasispecies spectrum reconstruction: Implements methods to assemble viral variants and estimate their frequencies from sequencing reads.
• Error correction: Applies an initial error correction mechanism to sequencing data to improve downstream assembly accuracy.
• Graph-based assembly: Constructs weighted read graphs and assembles quasispecies by identifying maximum-bandwidth paths to resolve closely related sequences.
• Frequency estimation via Expectation Maximization (EM): Uses EM algorithms to estimate the abundance of each reconstructed quasispecies.
• Performance and accuracy versus ShoRAH: Experimental comparisons with ShoRAH showed ViSpA reconstructs more viable sequences without internal stop codons and achieves higher fidelity on HCV and HIV datasets, with fewer mismatches and accurate open reading frames.

Scientific Applications:

• Viral evolution: Characterizes intra-host genetic diversity of RNA viruses to study evolutionary dynamics.
• Drug resistance analysis: Identifies low-frequency variants relevant to antiviral resistance.
• Chronic infection dynamics: Profiles quasispecies population structure in chronic infections to inform disease progression studies.
• HCV and HIV sequence analysis: Reconstructs frequent viral sequences and open reading frames from HCV and HIV high-throughput sequencing datasets.

Methodology:

Initial error correction of sequencing reads; construction of weighted read graphs and assembly via maximum-bandwidth path identification; frequency estimation using Expectation Maximization (EM).