Ye Zheng

InSpace quantifies subcellular organization by preserving localization and molecular co-occurrence, revealing spatial programs in B and plasma cells across cancers.

RAMP improves cross-platform proteomics analysis by preserving protein expression order, enhancing cell-type annotation and prediction across multiple cancer types.

FFPE-CUTAC is a new assay for analyzing FFPE tissues that provides regulatory and copy-number profiles, showing robustness over time and compatibility with RNA-seq.

This study links low stool valerate to CAR T-cell dysfunction in B-cell lymphoma and shows valerate supplementation improves CAR T function.

scanCT identifies disease-associated genomic feature groups using a tree-based framework applied to single-cell multi-omics COVID-19 data, revealing interpretable marker combinations.

This paper introduces a deep multiplexed imaging technique to profile up to 50 markers per circulating tumor cell, enhancing biomarker analysis for precision oncology.

ADTnorm normalizes and integrates CITE-seq datasets to remove batch effects and improve cell-type separation across 13 public datasets.

The paper shows that total whole-arm chromosome losses predict cancer outcomes across types, suggesting centromere breaks drive aneuploidy rather than mitotic errors.

The paper identifies RNA Polymerase II hypertranscription at histone genes in cancer FFPE samples, linking it to tumor progression and aneuploidy.

The paper identifies regulatory elements and chromatin structures in the RCA gene cluster, revealing long-range interactions and a TAD boundary within CR1 that influence gene expression and autoimmune disease susceptibility.

scGAD provides a dimension reduction tool for scHi-C data to explore gene-level chromatin interactions and integrate with other single-cell modalities.

This paper introduces BandNorm and 3DVI to normalize and de-noise scHi-C data, improving performance in cell type separation and 3D genomic structure recovery.

The paper identifies novel risk genes for autism spectrum disorder using transcriptome-wide transmission disequilibrium analysis across 7,805 ASD proband-parent trios.

This paper develops scCUT&Tag to profile H3K27me3 in single cells, distinguishing cell types in blood and identifying PcG activity changes in brain tumors before and after treatment.

FreeHi-C simulates high-fidelity Hi-C data for benchmarking and augmentation, improving detection precision while controlling false discovery rates.

mHi-C improves Hi-C analysis by handling multi-mapping reads, increasing sequencing depth and reproducibility of contact matrices and interactions.