Abstract
Background Recent advances in long-read callers and assembly methods have greatly facilitated structural variants (SV) detection via read-based and assembly-based detection strategies. However, the lack of comparison studies, especially for SVs at complex genomic regions, complicates the selection of proper detection strategy for ever-increasing demand of SV analysis.
Results In this study, we compared the two most widely-used strategies with six long-read datasets of HG002 genome and benchmarked them with well curated SVs at genomic regions of different complexity. First of all, our results suggest that SVs detected by assembly-based strategy are slightly affected by assemblers on HiFi datasets, especially for its breakpoint identity. Comparably, though read-based strategy is more versatile to different sequencing settings, aligners greatly affect SV breakpoints and type. Furthermore, our comparison reveals that 70% of the assembly-based calls are also detectable by read-based strategy and it even reaches 90% for SVs at high confident regions. While 60% of the assembly-based calls that are totally missed by read-based callers is largely due to the challenges of clustering ambiguous SV signature reads. Lastly, benchmarking with SVs at complex genomic regions, our results show that assembly-based approach outperforms read-based calling with at least 20X coverage, while read-based strategy could achieve 90% recall even with 5X coverage.
Conclusions Taken together, with sufficient sequencing coverage, assembly-based strategy is able to detect SVs more consistently than read-based strategy under different settings. However, read-based strategy could detect SVs at complex regions with high sensitivity and specificity but low coverage, thereby suggesting its great potential in clinical application.
Competing Interest Statement
The authors have declared no competing interest.