DisCVR

DisCVR detects known human viruses from high-throughput sequencing (HTS) data to enable rapid viral diagnosis of clinical samples.

Key Features:

• K-mer matching algorithm: Compares 22-nucleotide k-mers from sample HTS data against k-mers derived from taxonomically labeled viral genomes to identify viral genetic material.
• Validation and performance metrics: Validated on published HTS datasets of 89 adult upper respiratory tract infection clinical samples with reported sensitivity 79% and specificity 100% against real-time PCR and metagenomic analyses.
• Mixed infection detection: Identifies mixed viral infections within clinical samples via k-mer–based detection.
• Comparative analysis: Produced results comparable to a published metagenomic analysis of 177 blood samples from patients in Nigeria.

Scientific Applications:

• Diagnosis of viral infections: Enables detection of human viruses from HTS data to support clinical viral diagnosis.
• Surveillance and epidemiology: Facilitates simultaneous detection of multiple pathogens for outbreak monitoring and epidemiological investigations.
• Research on mixed infections: Supports investigation of co-infection dynamics by identifying multiple viral agents in the same sample.

Methodology:

Uses a k-mer matching approach that compares 22-nucleotide k-mers extracted from sample HTS reads to k-mers derived from taxonomically labeled viral genomes.