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.
Broad Institute of MIT and Harvard, Harvard University
Aviv Regev, PhD
Broad Institute of MIT and Harvard, Howard Hughes Medical Institute
Jimmie Ye, PhD
University of California, San Francisco