QuasiSeq: profiling viral quasispecies via self-tuning spectral clustering with PacBio long sequencing reads.

ABSTRACT:

Motivation

The existence of quasispecies in the viral population causes difficulties for disease prevention and treatment. High-throughput sequencing provides opportunity to determine rare quasispecies and long sequencing reads covering full genomes reduce quasispecies determination to a clustering problem. The challenge is high similarity of quasispecies and high error rate of long sequencing reads.

Results

We developed QuasiSeq using a novel signature-based self-tuning clustering method, SigClust, to profile viral mixtures with high accuracy and sensitivity. QuasiSeq can correctly identify quasispecies even using low-quality sequencing reads (accuracy <80%) and produce quasispecies sequences with high accuracy (≥99.55%). Using high-quality circular consensus sequencing rea

SUBMITTER: Jiao X 

PROVIDER: S-EPMC9890302 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature