Improving long-read somatic structural variant calling with pangenome and de novo personal genome assembly.
This project develops a long-read somatic structural variant (SV) calling framework that leverages pangenome graphs and de novo personal genome assembly to improve sensitivity and precision over reference-only pipelines (Qin et al., 2025).
Tumor genomes harbor SVs in repetitive, hypervariable, and low-mappability regions where reference-based callers systematically lose recall. By assembling each individual’s genome and comparing tumor and matched-normal reads against pangenome-aware coordinates, the method recovers complex somatic events including large indels, mobile element insertions, and tandem duplications. Source code is available on GitHub. Related publications include colorSV for long-range somatic SV calling from co-assembly graphs (Le et al., 2025) and LongcallD for joint calling and phasing of small, structural, and mosaic variants from long reads (Gao et al., 2026).
References
2026
bioRxiv
LongcallD: joint calling and phasing of small, structural and mosaic variants from long reads
Yan Gao, Wen-Wei Liao, Qian Qin, and 2 more authors
@article{Gao2026LongcallD,title={{LongcallD}: joint calling and phasing of small, structural and mosaic variants from long reads},author={Gao, Yan and Liao, Wen-Wei and Qin, Qian and Hall, Ira M and Li, Heng},journal={bioRxiv},pages={2026.03.20.713111},month=mar,year={2026},doi={10.64898/2026.03.20.713111},}
2025
bioRxiv
Improving long-read somatic structural variant calling with pangenome and de novo personal genome assembly
@article{Qin2025LongReadSV,title={Improving long-read somatic structural variant calling with pangenome and de novo personal genome assembly},author={Qin, Qian and Heinz, Jakob and Li, Heng},journal={bioRxiv},pages={2025.10.28.685154},month=oct,year={2025},doi={10.1101/2025.10.28.685154},}
@article{Le2025colorSV,title={{colorSV}: Long-range Somatic Structural Variation Calling from Matched Tumor-normal Co-assembly Graphs},author={Le, M K and Qin, Qian and Li, Heng},journal={Genomics, Proteomics \& Bioinformatics},pages={qzaf082},month=sep,year={2025},doi={10.1093/gpbjnl/qzaf082},}