American Statistical Association, Statistical Learning and Data Science Section
Title
Integrated analysis of single-cell data across technologies, patients, and perturbations
Abstract
As single-cell sequencing becomes increasingly routine, multimodal, perturbation, and clinical datasets represent exciting new frontiers. I will present new computational methods and experimental technologies that we are developing to improve organism-wide cell type annotation (Pan-Human Azimuth), interpret global transcriptomic phenotypes (RNA Fingerprinting), and quantify variation across individuals and developmental contexts (scSLIDE). scSLIDE addresses a key limitation of standard case-control analyses by representing each sample as a distribution over cellular states, enabling direct reconstruction of sample-level trajectories from single-cell data. We demonstrate how this framework can recover molecular axes of progression in Alzheimer’s disease that align with pathology-based estimates of neurodegeneration, identifying a robust and reproducible trajectory of neurodegeneration that is missed by standard differential expression analyses.
Presenter
Rahul Satija, PhD, is a Core Faculty Member at the New York Genome Center (NYGC), with a joint appointment as Professor at the Center for Genomics and Systems Biology at New York University (NYU). Prior to joining the NYGC, Dr. Satija was a postdoctoral researcher at the Broad Institute of Harvard and MIT, where he developed new methods for single cell analysis. The Satija Lab focuses on developing computational and experimental methods to sequence and interpret the molecular contents of a single cell. His Lab applies single cell genomics to understand the causes and consequences of cell-to-cell variation, with a particular focus on immune regulation and early development. Dr. Satija is a recipient of the NIH New Innovator Award, and in 2020 was selected to direct an NIH Center for Excellence in Genomic Science. Dr. Satija holds a BS degree in Biology and Music from Duke University, and obtained his PhD in Statistics from Oxford University as a Rhodes Scholar.
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Highlights
- 1 hour 30 minutes
- Online