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Pseudo-temporal ordering of individual cells reveals regulators of differentiation

GSE52529 Homo sapiens Expression profiling by high throughput sequencing 384 samples Submitted 2014/03/23 Platform GPL11154Platform GPL16791
Summary
Single-cell expression profiling by RNA-Seq promises to exploit cell-to-cell variation in gene expression to reveal regulatory circuitry governing cell differentiation and other biological processes. Here, we describe Monocle, a novel unsupervised algorithm for ordering cells by progress through differentiation that dramatically increases temporal resolution of expression measurements. This reordering unmasks switch-like changes in expression of key regulatory factors, reveals sequentially organized waves of gene regulation, and exposes regulators of cell differentiation. A functional screen confirms that a number of these regulators dramatically alter the efficiency of myoblast differentiation, demonstrating that single-cell expression analysis with Monocle can uncover new regulators even in well-studied systems.
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Also filed as BioProject PRJNA229164 and SRA study SRP033135. Searching any of these in the dataset finder brings you back here.

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