㽶Ƶ

Event

QLS Seminar Series - Rahul Satija

Tuesday, October 15, 2019 12:00to13:00
McIntyre Medical Building Room 1034, 3655 promenade Sir William Osler, Montreal, QC, H3G 1Y6, CA

Integrated analysis of single-cell data across technologies and modalities

Rahul Satija, New York Genome Center
Tuesday October 15, 12-1pm
McIntyre Medical Building, room 1034

Abstract: Single cell transcriptomics (sc㽶Ƶ-seq) has transformed our ability to discover and annotate cell types and states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, including high-dimensional immunophenotypes, chromatin accessibility, and spatial positioning, a key analytical challenge is to integrate these datasets into a harmonized atlas that can be used to better understand cellular identity and function. Here, we develop a computational strategy to “anchor” diverse datasets together, enabling us to integrate and compare single cell measurements not only across sc㽶Ƶ-seq technologies, but different modalities as well. After demonstrating substantial improvement over existing methods for data integration, we anchor sc㽶Ƶ-seq experiments with scATAC-seq datasets to explore chromatin differences in closely related interneuron subsets, and project single cell protein measurements onto a human bone marrow atlas to annotate and characterize lymphocyte populations. Lastly, we demonstrate how anchoring can harmonize in-situ gene expression and sc㽶Ƶ-seq datasets, allowing for the transcriptome-wide imputation of spatial gene expression patterns, and the identification of spatial relationships between mapped cell types in the visual cortex. Our work presents a strategy for comprehensive integration of single cell data, including the assembly of harmonized references, and the transfer of information across datasets.

Back to top