Weiqiu Cheng

The paper introduces FICTURE2, a statistical model that infers transcriptional programs from individual RNA molecules in spatial transcriptomics data, revealing spatial organization and cellular identity without segmentation.

This study combines histopathology and spatial transcriptomics to show that mTORC1 hyperactivation causes fiber-type-specific pathological changes in skeletal muscle.

Seq-Scope-X improves spatial transcriptomics resolution by expanding tissues, revealing detailed nuclear and cytoplasmic transcriptome differences in liver cells and enabling proteomic analysis in other tissues.

This paper describes a protocol to repurpose Illumina sequencing flow cells for high-resolution spatial transcriptomics, enabling detailed spatial gene expression analysis with improved resolution and cost efficiency.

FICTURE provides a scalable segmentation-free method for analyzing high-resolution spatial transcriptomics data, revealing detailed tissue architecture in complex regions.

MiXeR-Pred improves polygenic prediction by leveraging genetic overlap between complex phenotypes, outperforming primary GWAS and MTAG approaches.

This study identifies 14 novel opioid use disorder loci and 7 shared loci with schizophrenia, bipolar disorder, and major depression using genome-wide association summary statistics.

The paper introduces Meta-MOSTest, an extension of MOSTest for meta-analysis of multivariate GWAS, showing it maintains statistical power and type I error control across multiple cohorts.

This study uses a multivariate genetic approach to analyze personality and cognitive traits, identifying pleiotropy and improving polygenic prediction.

The paper uses a multivariate GWAS approach to identify 780 genetic loci associated with cortical morphology, showing a 10-fold increase in loci compared to univariate methods.