AMS Weekly Seminar | Rahul Satija

Location: Shaffer 3

When: April 30th at 1:30 p.m.

Title: Integrated analysis of single-cell data across modalities, technologies, and perturbations

Abstract: Single-cell genomics is generating data at an unprecedented scale, creating new statistical challenges centered on how to integrate increasingly heterogeneous datasets and how to draw causal insight from rich but largely observational measurements. In this talk, I will highlight two complementary advances that address these problems using reference-based statistical frameworks to interpret complex single-cell data. First, I will describe RNA fingerprinting, a framework for causal inference using single-cell perturbation dictionaries. Large-scale perturbation atlases systematically measure how cells respond to genetic and chemical perturbations, enabling causal interpretation of new experiments. RNA fingerprinting learns denoised perturbation “fingerprints” from reference data, then probabilistically maps cells from new datasets to candidate perturbations while accounting for uncertainty. This approach supports accurate single-cell assignments, scales to genome-wide screens, and resolves combinatorial perturbations, linking observed cellular states to their likely upstream drivers. Second, I will describe bridge integration, a framework for integrating data across molecular modalities. Because most reference datasets are built from single-cell RNA-seq, they cannot be directly used to interpret experiments that do not measure gene expression. Bridge integration addresses this limitation by using multi-omic datasets as molecular bridges, creating a shared latent space that enables harmonization across transcriptomic, epigenetic, and protein measurements. Together, these frameworks are steps towards a broader goal of transitioning single-cell genomics to not only catalogue cellular diversity, but to help understand and explain the molecular forces that shape it.

Bio: 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 in2020 was selected to direct an NIH Center for Excellence in Genomic Science.

Zoom link: https://jh.zoom.us/j/98439727148?pwd=Fe6LvWorGt3JdoJmW4mPwzdiBjR5F7.1#success