Huiwen Che

The paper mitigates genotype-driven bias in single-cell DNA methylation analysis by masking variant positions, improving clustering and reducing spurious methylation differences in pooled datasets.

The paper analyzes cfDNA methylome and fragmentome profiles from healthy individuals to identify cell-type and demographic signatures influencing cfDNA characteristics.

The paper develops a method to detect and type cancer using cfDNA sequencing data, achieving 81.62% accuracy in distinguishing malignant from control samples.

The paper performs de novo assembly of two Swedish genomes, identifies novel sequences absent from GRCh38, and shows improved variant calling with these sequences.

SweGen provides a high-quality whole-genome map of genetic variation in the Swedish population, useful for clinical genetics and association studies.