Characterization of the single-cell transcriptional landscape by highly multiplex RNA-Seq

ABSTRACT: Our understanding of the development and maintenance of tissues has been greatly aided by large-scale gene expression analysis. However, tissues are invariably complex, and expression analysis of a tissue confounds the true expression patterns of its constitutent cell types. Here we propose a novel strategy to access such complex samples. Hundreds of single-cell RNA-Seq expression profiles were generated, and clustered to form a two-dimensional cell map onto which expression data was projected. The resulting cell map integrates three levels of organization: the whole population of cells, the functionally distinct subpopulations it contains, and the single cells themselvesM-bM-^@M-^Tall without need for known markers to classify cell types. The feasibility of the strategy is demonstrated by

ORGANISM(S): Mus musculus

SUBMITTER: Sten Linnarsson 

PROVIDER: E-GEOD-21180 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress