Deyou Zheng

This study uses single-nucleus transcriptomics to show that perinatal SERT expression in CA3 pyramidal neurons affects gene expression in specific brain regions, with implications for social and spatial circuit development and autism-related genes.

This study shows that ZFP281 expression delays breast cancer initiation and prevents metastasis by enforcing a dormant state in cancer cells.

This study uses scRNA-seq to analyze murine osteosarcoma models and identifies Skp2's role in metastasis, genomic instability, and immune activation, revealing potential therapeutic targets.

This study shows that H2AK119ub dynamics regulate hair follicle stem cell quiescence by repressing proliferation-promoting programs and maintaining quiescence through inhibitory niche signaling.

shinyUMAP is an online tool that allows users to upload single cell data and interactively generate UMAPs with different parameters to better understand cell cluster relationships.

This paper shows that binarizing scRNA-seq data and integrating it with scATAC-seq data using TF-IDF and LSI improves clustering for multiomic analysis.

The paper shows that TAD hierarchy restricts LTR activation, and its loss in cancer allows LTRs to act as alternative promoters, driving oncogene activation and transcriptional diversity.

The paper uses zebrafish developmental lineage tracing and single-cell RNA sequencing to show that early HSPCs favor lymphoid lineage while later HSPCs skew towards erythroid, with early HSPCs contributing to adult lymphocytes.

This study shows aging reduces lung stem cell function and suppresses lung cancer by inducing iron deficiency through the NUPR1-lipocalin-2 pathway.

This study uses single-cell RNA sequencing to analyze the role of Six3 and Six6 in retinal progenitor cell differentiation, identifying altered developmental trajectories and gene regulation in their dual deficiency.

scDAPP provides an automated R-based pipeline for comparative single-cell transcriptomics analysis across groups, generating comprehensive results and visualizations.

This study uses single-cell RNA-seq in cerebral organoids to analyze CHD8 heterozygous mutations, identifying altered gene expression, cell composition, and cell-cell communication linked to autism risk.

The paper uses metacells to analyze scRNA-seq data from COVID-19 patient PBMCs, identifying cell-type specific temporal gene response programs.

This study identifies NR2F1 as a key regulator of dormancy in uveal melanoma by epigenetically suppressing oncogenic Gαq/11-YAP signaling and cell cycle genes.

The paper develops NuHash, a method for multiplexing snATAC-seq using oligonucleotide-conjugated antibodies, achieving high demultiplexing accuracy with human and mouse samples.

The paper identifies chromatin regulatory genes as genetic modifiers of conotruncal heart defects in 22q11.2 deletion syndrome and links them to sporadic congenital heart disease.

The paper uses single-cell RNA-sequencing to study how Tbx1 inactivation affects cardiac neural crest cell differentiation and aortic arch development in mice.

This study identifies ultra-rare genetic variants in PANS patients through exome and whole genome sequencing, revealing candidate genes involved in both immune and neuronal pathways.

This study uses single cell RNA-seq data to analyze cell-cell communication differences in autistic brains compared to controls, identifying altered signaling pathways involving neurons and glia.

This study identifies a Tbx1-dependent multilineage primed population in the murine cardiopharyngeal mesoderm using single-cell RNA-sequencing and shows its role in cardiac and skeletal muscle development.

This study shows that reducing CSF-2 in Csf1r+/- mice rescues behavioral and histopathological deficits in ALSP by preventing microgliosis and transcriptomic changes, suggesting CSF-2 as a therapeutic target.

The paper constructs gene co-expression networks in mouse cardiomyocytes to identify spatiotemporal gene modules and regulatory pathways involved in cardiac morphogenesis.

SMARTcleaner identifies and removes off-target signals in SMART ChIP-seq data, improving peak calling and downstream analysis.

RISC integrates scRNA-seq datasets with overlapping cell clusters using PCR, improving accuracy in datasets with similar cell types but distinct functional states.

The paper identifies enriched gene expression in inhibitory neurons for autism spectrum disorder (ASD) candidates using single-cell transcriptomic data, supporting the E/I imbalance hypothesis.