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Massively parallel single-cell RNA-Seq for dissecting cell type and cell state compositions

GSE54006 Mus musculus Expression profiling by high throughput sequencing 28 samples Submitted 2014/02/14 Platform GPL13112
Summary
In multi-cellular organisms, biological function emerges when cells of heterogeneous types and states are combined into complex tissues. Nevertheless unbiased dissection of tissues into coherent cell subpopulations is currently lacking. We introduce an automated, massively parallel single cell RNA sequencing method for intuitively analyzing in-vivo transcriptional states in thousands of single cells. Combined with unsupervised classification algorithms, it facilitates ab initio and marker-free characterization of classical hematopoietic cell types from splenic tissues. Importantly, modeling single cells transcriptional states in dendritic cells subpopulations, where a cell type hierarchy is difficult to define with marker-based approaches, uncovers complex combinatorial activity of multiple gene modules and capture cell-to-cell variability in steady state conditions and following pathogen activation. Massively parallel single cell RNA-seq thereby emerges as an effective tool for unbiased dissection of complex tissues.
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Direct links to NCBI, no account and no request form: the whole study as GSE54006_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 28 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA234330 and SRA study SRP035326. Searching any of these in the dataset finder brings you back here.

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