Brett David McKinnon

The paper characterizes human endometrial stem/progenitor cells using scRNA-seq, identifying key markers and signaling pathways involved in their function and interactions.

The paper uses deconvolution on bulk RNA-seq data to identify cell type proportions and expression signatures linked to endometrial function and disease in women with and without endometriosis.

This study identifies M2 macrophages and IL1 signaling as key mediators of endometriosis risk and shows their pleiotropic role in comorbid traits.

The paper creates a large single-cell endometrial atlas and uses AI to identify gene expression and receptor-ligand changes associated with endometriosis, developing predictive models for disease severity.

scSplit demultiplexes pooled single-cell RNA-Seq samples using genetic differences inferred from the data, showing high accuracy and consistency with known truths.