Dylan Kotliar

The paper identifies an age-related expansion of an inflammatory and quiescent HSC subpopulation using integrated single-cell data.

The paper introduces TCAT, a pipeline to annotate T-cell GEPs, identifying 46 reproducible programs across diverse tissues and diseases.

The paper identifies three regulatory variants associated with IVD expression and linked to GWAS signals, showing synergistic and opposing effects through functional experiments.

Sciviewer allows interactive visualization of single-cell RNA-Seq data within Python, enabling seamless integration between visual exploration and programmatic analysis.

This paper introduces cNMF, a matrix factorization method to disentangle cell-type identity and activity programs from scRNA-Seq data, showing it improves cell type hierarchy and identifies novel activity programs.

The paper introduces a method to detect directional effects of transcription factor binding on disease risk using GWAS data and applies it to identify new causal genes and mechanisms.