Fengxiao Bu

Calibration and refinement of ACMG/AMP criteria for variant classification with BayesQuantify

BayesQuantify refines ACMG/AMP variant classification criteria using Bayesian methods, providing objective thresholds for evidence levels across multiple datasets.

Whole-Genome Sequencing Pilot Study of the Central Asian Genetic Diversity Project Reveals Distinct Genetic Histories, Adaptive Processes, and Introgression Events

This study uses whole-genome sequencing of Central Asians to reveal genetic diversity, admixture events, and adaptive processes shaping their demographic history and medical relevance.

Helicobacter pylori genome aggregation database reveals complex evolutionary forces shaping its genomic landscape and clinical impact in East Asia

The paper introduces HPgnomAD, a global H. pylori genome database revealing evolutionary patterns and clinical implications in East Asia.

RGnet: Recessive Genotype Network in a Large Mendelian Disease Cohort

RGnet identifies pathogenic variants in recessive disorders by analyzing genotype networks in a large cohort of hearing loss cases.

GDC: An Integrated Resource to Explore the Pathogenesis of Hearing Loss through Genetics and Genomics

The paper introduces GDC, a database integrating genetic and genomic data to study hearing loss, identifying novel mutational hotspots and candidate genes.

Frameshift variants in TBX2 underlie autosomal-dominant hearing loss with incomplete penetrance of nystagmus

The paper identifies TBX2 frameshift variants as the cause of autosomal-dominant hearing loss with incomplete nystagmus penetrance, validated through linkage analysis, sequencing, and mouse models.

Identification of mobile element insertion from whole genome sequencing data using deep neural network model

The paper introduces DeepMEI, a deep learning tool for identifying mobile element insertions from whole-genome sequencing data, finding it outperforms existing methods and discovers more non-reference MEIs in 1000 Genome Project samples.

seGMM: a new tool to infer sex from massively parallel sequencing data

seGMM infers sex from sequencing data with >99% accuracy, outperforming existing tools by incorporating Y chromosome features.

High performance of a GPU-accelerated variant calling tool in genome data analysis

This study evaluates BaseNumber, a GPU-accelerated variant calling tool, showing high accuracy and speed compared to GATK on WGS data from multiple sources.