Mountain View
biomedical and healthCAre Data Discovery Index Ecosystem
help Advanced Search
Title: Characterization of the single-cell (ES and MEF) transcriptional landscape by highly multiplex RNA-Seq      
dateReleased:
05-24-2011
description:
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 describe a novel strategy to access such complex samples. 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 themselves—all without need for known markers to classify cell types. The feasibility of the strategy was demonstrated by analyzing the complete transcriptomes of 92 single cells of two distinct types. We believe this strategy will enable the unbiased discovery and analysis of naturally occurring cell types during development, adult physiology and disease. 92 single cells (48 mouse ES cells, 44 mouse embryonic fibroblasts and 4 negative controls) were analyzed by single-cell tagged reverse transcription (STRT)
privacy:
not applicable
aggregation:
instance of dataset
ID:
E-GEOD-29087
refinement:
raw
alternateIdentifiers:
29087
keywords:
functional genomics
dateModified:
05-02-2014
availability:
available
types:
gene expression
name:
Mus musculus
accessURL: https://www.ebi.ac.uk/arrayexpress/files/E-GEOD-29087/E-GEOD-29087.raw.1.zip
storedIn:
ArrayExpress
qualifier:
gzip compressed
format:
TXT
accessType:
download
authentication:
none
authorization:
none
accessURL: https://www.ebi.ac.uk/arrayexpress/files/E-GEOD-29087/E-GEOD-29087.processed.1.zip
storedIn:
ArrayExpress
qualifier:
gzip compressed
format:
TXT
accessType:
download
authentication:
none
authorization:
none
accessURL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29087
storedIn:
Gene Expression Omnibus
qualifier:
not compressed
format:
HTML
accessType:
landing page
primary:
true
authentication:
none
authorization:
none
abbreviation:
EBI
homePage: http://www.ebi.ac.uk/
ID:
SCR:004727
name:
European Bioinformatics Institute
homePage: https://www.ebi.ac.uk/arrayexpress/
ID:
SCR:002964
name:
ArrayExpress

Feedback?

If you are having problems using our tools, or if you would just like to send us some feedback, please post your questions on GitHub.