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

ABSTRACT: 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 multipl

ORGANISM(S): Mus musculus

SUBMITTER: Ido Amit 

PROVIDER: E-GEOD-54006 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress