Deciphering Intra- and Inter-Individual Variation at Single Cell Resolution
With a goal of understanding how non-coding genetic variation in humans functionally impacts disease traits, this network proposes a framework to map and interpret intra- and inter-individual variation in complex tissues using single cell approaches.
Results & Resources
This project developed new computational tools to quantify cellular variation at single-cell resolution. SHARE-seq is a scalable approach to measure chromatin accessibility and gene expression within the same single cell, and AtacWorks, a method to denoise and identify accessible chromatin regions from low-coverage or low-quality ATAC-seq data. With these tools, they studied the mouse neocortex neuronal plasticity and circuit integration, and are currently performing studies on the human heart.