Integrating single-cell transcriptomic data across different conditions, technologies, and species
Abstract
Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the...
Paper Details
Title
Integrating single-cell transcriptomic data across different conditions, technologies, and species
Published Date
Apr 2, 2018
Journal
Volume
36
Issue
5
Pages
411 - 420
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