Edward Sanders

The paper develops a machine learning framework to assess quality of chromatin accessibility bigWig tracks using biologically relevant features and internal controls.

REgulamentary is a tool for cell-type specific annotation of cis-regulatory elements, outperforming existing methods and applied to GWAS data to prioritize causal variants.

REnformer predicts chromatin accessibility from single-cell ATAC-seq data, outperforming Enformer in accuracy and error rates, and validates its utility with a known thalassemia variant.

The paper shows that active enhancers recruit cohesin to form cell-specific chromatin domains, using the alpha globin cluster as a model.