Wanqiu Chen

This study shows prenatal e-cigarette exposure causes region- and cell type-specific metabolic and developmental changes in neonatal rat brains, linked to neurodevelopmental disease risk.

This study shows that prenatal THC exposure disrupts mitochondrial gene programs and medium spiny neuron maturation in the nucleus accumbens using snRNA-seq and snATAC-seq in a rat model.

This study shows that astrocytic D1 dopamine receptors in the nucleus accumbens shell regulate synaptic remodeling and cocaine seeking behavior in mice.

This study benchmarks five scCNV inference methods across multiple scRNA-seq platforms and mixed samples, finding variations in performance based on data characteristics and batch effects.

This study uses spatial transcriptomics on FFPE kidney biopsy tissues to identify distinct transcriptomic signatures for different types of kidney transplant rejections.

The paper provides comprehensive reference materials with genomic, epigenomic, transcriptomic, scRNA-seq, and proteomic characterizations of two cell lines for benchmarking and validation.

This study develops a patient-derived model of cisplatin resistance in ovarian cancer stem-like cells and identifies molecular and functional changes associated with resistance.

The paper presents whole-genome and whole-exome sequencing datasets from a multi-center, cross-platform study to benchmark NGS technologies and bioinformatics pipelines in cancer genomics.

The paper establishes reference samples with high-coverage whole-genome sequencing to create truth sets for somatic mutation and germline variant detection using NGS technologies.

This study evaluates reproducibility and accuracy of cancer mutation detection using whole-genome and whole-exome sequencing across multiple sequencing centers and bioinformatics pipelines.

This study benchmarks seven SARS-CoV-2 whole-genome sequencing protocols using patient samples, finding performance differences based on viral input and sequencing parameters.

This study compares somatic mutation detection accuracy using personalized genome assembly versus standard reference in cancer samples, showing improved results with personalized assemblies.

This study evaluates somatic CNV callers using NGS data from 91 samples with varying factors, finding that caller choice and tumor purity significantly impact call quality.

The paper presents a multi-center cross-platform scRNA-seq reference dataset for benchmarking bioinformatics methods across different platforms and centers.

This study benchmarks scRNA-seq reproducibility across platforms and pipelines, finding that batch correction methods significantly affect results.