Yuwei Zhang

This study evaluates diploid donor-specific assemblies for improving somatic structural variant detection in cancer genomes, finding they identify more variants and reduce artifacts compared to standard references.

The paper benchmarks somatic variant and indel detection at low allele fractions using short- and long-read data, finding sensitivity and precision around 80% at 300x coverage.

The paper benchmarks somatic structural variant detection at ultra-low allele fractions using synthetic data and evaluates 12 pipelines, finding long-read sequencing provides higher accuracy than short-read methods.

HiScanner detects high-resolution copy number alterations in single cells, outperforming existing methods and revealing distinct CNA patterns in neurons and oligodendrocytes.

SeCNV improves copy number profiling in single-cell DNA sequencing by using structural entropy, achieving high accuracy and efficiency on large datasets.