Mengjie Chen

This paper introduces RAD-seq, a method to quantify RNA accessibility by protein binding, and shows it can detect RBP footprints and RNA structure changes under stress.

The paper shows that acetate from gut microbiota maintains acetyl-CoA levels in colonic epithelial cells, preventing age-independent senescence and inflammation.

The paper reveals an m6A-dependent mechanism where microRNAs bind chromatin-associated RNAs to activate transcription by recruiting chromatin remodelers and demethylases.

scPrediXcan improves transcriptome-wide association studies by integrating deep learning for cell-type-specific gene expression prediction, identifying more causal genes and explaining more GWAS loci in type 2 diabetes and systemic lupus erythematosus.

The paper introduces a gene expression stability metric, the gene homeostasis Z-index, to identify genes under active regulation in different organs and highlights its advantage over traditional mean-based methods.

This paper identifies four major challenges in single-cell differential expression analysis and proposes a novel paradigm to address them.

The paper introduces a physical model and improved analysis methods for quantifying protein complexes from Prox-seq data, enhancing accuracy and robustness.

This study generates single-cell RNA and ATAC sequencing data from postmenopausal human fallopian tubes and ovaries, revealing distinct cell types and regulatory landscapes with implications for gynecologic diseases.

KAS-pipe2 is a toolkit for analyzing KAS-seq and spKAS-seq data, offering quality control, alignment, differential activity analysis, and novel features for studying transcription and R-loops.

The paper analyzes whole-genome data from Nigerian breast cancer patients, identifying ethnic-driven somatic evolution and distinct genomic subtypes associated with African ancestry.

The paper introduces CARseq, a framework for RNA-seq differential expression analysis that accounts for cell type composition, showing higher power and accuracy in identifying differentially expressed genes in schizophrenia and autism studies.

Dmatch aligns scRNA-seq datasets to reduce batch effects without over-correction, enabling cell-type-specific comparisons and eQTL mapping.

This paper challenges the notion of 'drop-outs' in scRNA-seq data by showing that resolving cell-type heterogeneity reduces zeros and proposes a new framework for UMI analysis.

REPIC compiles and provides access to m6A methylation data from 672 samples across 11 organisms, integrating it with histone and chromatin data for comprehensive analysis.

RADAR is a tool for differential methylation analysis of MeRIP-seq data, showing improved accuracy and reproducibility compared to existing methods.

The paper identifies allele-specific open chromatin (ASoC) variants in human iPSC-derived neurons and shows their strong enrichment in brain disorder risk variants.

This paper introduces PQLseq, a method for heritability estimation and differential analysis in genomic sequencing studies, showing it provides unbiased heritability estimates and better power for differential analysis.

This paper introduces scPLS, a method to control confounding effects in scRNA-seq by jointly modeling control and target genes, showing improved performance over existing methods.