Coval

Coval improves the accuracy of short-read alignments to enhance detection of DNA polymorphisms from next-generation sequencing (NGS) data.

Key Features:

• Minimization of Spurious Alignments: Filters out mismatched reads that persist after local realignment and error correction to reduce spurious alignments in short-read mappings.
• Error Correction Based on Base Quality and Allele Frequency: Applies error correction using base quality scores and allele frequency at non-reference positions in individual or pooled samples.
• Validation on Simulated and Experimental Data: Has been applied to simulated genomes and short-read datasets from rice, nematode, and mouse to evaluate performance.
• Targeted Alignment Improvement: Eliminates incorrectly mapped reads in targeted alignments where whole-genome sequencing reads are aligned to local genomic segments.

Scientific Applications:

• SNP and Indel Identification: Enhances the accuracy of single nucleotide polymorphism (SNP) and insertion-deletion (indel) detection by improving alignment fidelity.
• Variant Calling Enhancement: Increases calling accuracy of existing short-read aligners and variant callers by reducing alignment- and sequencing-error–driven false calls.
• Research in Genomics, Evolutionary Biology, and Personalized Medicine: Supports studies that require precise variant detection across diverse organisms and experimental contexts.

Methodology:

Performs local realignment followed by error correction based on base quality scores and allele frequency, then filters mismatched reads that remain after correction.