Siyuan Ma

This paper evaluates the statistical validity of synthetic biomedical images and introduces PAMS to improve biological inference.

The paper creates a spatial atlas of early-stage colorectal cancer tumors to identify bacterial niches and their impact on tumor transcriptomes, highlighting C. difficile's significant influence despite low abundance.

BASSL-MI uses self-supervised learning to identify clinically relevant tumor niches in multiplexed imaging without requiring cell segmentation.

This study compares the gut microbiome and butyrate levels in children with asymptomatic C. difficile colonization and symptomatic CDI, finding distinct microbial and butyrate profiles associated with symptom status.

This study identifies cell type-specific DNA methylation changes in airway epithelial cells linked to early-life RSV infection and their association with subsequent wheezing.

The paper uses single-cell RNA sequencing to study how wheeze and early-life RSV infection affect airway epithelial development in children.

This paper introduces CompDA, a new method for health-microbiome association analysis that accounts for compositional data and ecological interactions, and demonstrates its effectiveness through simulations and real-data applications.

GammaGateR provides a semi-automated marker gating tool for multiplexed imaging data, improving consistency and reducing manual effort while revealing biological signals.

This paper introduces Robseq, a statistical model for RNA-Seq differential expression that addresses FDR inflation caused by group heteroscedasticity, showing improved control of false discovery and type-I error rates.

The paper introduces a statistical model to simulate microbial community profiles and evaluates its performance in benchmarking analysis methods.

The paper develops MMUPHin for meta-analysis of microbial communities in IBD, identifying consistent microbial associations and showing no discrete microbiome types.