Alper Eroğlu

The paper maps the human immune system across the lifespan using scRNA-seq and snATAC-seq, revealing unique infant immune signatures and age-related changes in immune cell populations.

This study uses longitudinal scRNAseq to analyze temporal dynamics of the tumor microenvironment in mouse breast tumors, identifying three patterns of multi-cellular phenotypic changes during progression.

CoRE-ATAC is a deep learning model that classifies regulatory elements from ATAC-seq data, accurately predicting cis-RE functions across multiple cell types and identifying cell-specific variations in regulatory activity.

This paper introduces ATAC-DoubletDetector, a read count-based method to detect multiplets in snATAC-seq data and annotate their cellular origins, achieving 85% accuracy in annotation.