SVsearcher

SVsearcher detects structural variations (SVs — genomic rearrangements >50 bp) in long-read sequencing data from Oxford Nanopore Technologies (ONT) and PacBio, improving SV discovery accuracy for studies of genetic disease and evolution.

Key Features:

• Supported data types: Processes long-read sequencing data from Oxford Nanopore Technologies (ONT) and PacBio.
• SV types and size range: Detects structural variations including deletions, insertions, and inversions larger than 50 base pairs.
• Error-aware detection: Addresses alignment errors caused by high ONT error rates, particularly in repetitive regions and multi-allelic SV loci.
• Benchmark performance: Demonstrated improved F1 scores by approximately 10% for high-coverage (50×) datasets and more than 25% for low-coverage (10×) datasets in comparative analyses on three real datasets.
• Multi-allelic SV recovery: Identifies a substantially higher proportion of multi-allelic SVs (81.7%–91.8%) compared to Sniffles and nanoSV (13.2%–54.0%).
• Comparative analysis: Evaluated against existing long-read SV callers (Sniffles, nanoSV) using real datasets.

Scientific Applications:

• Genetic disease research: Enables more accurate detection of SVs relevant to genetic disease studies.
• Evolutionary genomics: Facilitates identification of structural rearrangements for evolutionary analyses.
• Comprehensive SV discovery: Improves recovery of multi-allelic and complex SVs for thorough genomic characterization.

Methodology:

Performs SV detection from ONT and PacBio long reads while accounting for alignment errors in repetitive and multi-allelic regions and was evaluated by comparative analyses on three real datasets reporting F1 score improvements.