Molecular signatures of heterogeneous stem cell populations are resolved by linking single cell functional assays to single cell gene expression
Transcriptomics Dataset
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General Information
AccessionGSE61533
TitleMolecular signatures of heterogeneous stem cell populations are resolved by linking single cell functional assays to single cell gene expression
DescriptionThe discovery of significant heterogeneity in the self-renewal durability of adult haematopoietic stem cells (HSCs) has challenged our understanding of the molecules involved in population maintenance throughout life. Gene expression studies in bulk populations are difficult to interpret since multiple HSC subtypes are present and HSC purity is typically less than 50%% of the input cell population. Numerous groups have therefore turned to studying gene expression profiles of single HSCs, but again these studies are limited by the purity of the input fraction and an inability to directly ascribe a molecular program to a durable self-renewing HSC. Here we combine single cell functional assays with flow cytometric index sorting and single cell gene expression assays to gain the first insight into the gene expression program of HSCs that possess durable self-renewal. This approach can be used in other stem cell systems and sets the stage for linking key molecules with defined cellular functions.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61533
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

Dataset Accession
Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE61533
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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