Improving Long-Read Somatic Structural Variant Calling with Pangenome and De Novo Personal Genome Assembly.

UNLABELLED: Accurate detection of mosaic and somatic structural variants (SV) provides early diagnostic and therapeutic evidence for cancers. Although long-read whole-genome sequencing leads to more accurate SV detection than short-read sequencing, existing long-read SV callers only look at alignment against a single reference genome and are susceptible to systematic false discovery caused by germline differences between the individual genome and the reference genome. In this study, we develop a new SV filtering method that jointly considers the alignment against a pangenome and the de novo assembly of the germline genome. It dramatically reduces false-positive mosaic and somatic SVs in cancer cell lines with little loss in sensitivity for existing long-read SV callers. Our study highlights the essential need for pangenome or personal genome assembly to integrate SV calls for both SV discoveries and clinical diagnostics.

SIGNIFICANCE: We introduced a novel long-read SV filtering method that leverages pangenome and personal genome data and greatly improves the accuracy of somatic SV calling.