Literature DB >> 25657253

Expression profiling. Combinatorial labeling of single cells for gene expression cytometry.

H Christina Fan1, Glenn K Fu1, Stephen P A Fodor2.   

Abstract

We present a technically simple approach for gene expression cytometry combining next-generation sequencing with stochastic barcoding of single cells. A combinatorial library of beads bearing cell- and molecular-barcoding capture probes is used to uniquely label transcripts and reconstruct the digital gene expression profile of thousands of individual cells in a single experiment without the need for robotics or automation. We applied the technology to dissect the human hematopoietic system and to characterize heterogeneous response to in vitro stimulation. High sensitivity is demonstrated by detection of low-abundance transcripts and rare cells. Under current implementation, the technique can analyze a few thousand cells simultaneously and can readily scale to 10,000s or 100,000s of cells.
Copyright © 2015, American Association for the Advancement of Science.

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Year:  2015        PMID: 25657253     DOI: 10.1126/science.1258367

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  148 in total

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3.  Linking the T cell receptor to the single cell transcriptome in antigen-specific human T cells.

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Review 4.  Comparative analysis of murine T-cell receptor repertoires.

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5.  High-throughput full-length single-cell mRNA-seq of rare cells.

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Review 6.  Advances and applications of single-cell sequencing technologies.

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Journal:  Mol Cell       Date:  2015-05-21       Impact factor: 17.970

Review 7.  Advancing Cancer Research and Medicine with Single-Cell Genomics.

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8.  Single-cell systems biology: probing the basic unit of information flow.

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Journal:  Curr Opin Syst Biol       Date:  2017-12-06

Review 9.  Quantitative imaging of lipid droplets in single cells.

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Journal:  Analyst       Date:  2019-01-28       Impact factor: 4.616

Review 10.  RNA-Seq methods for transcriptome analysis.

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Journal:  Wiley Interdiscip Rev RNA       Date:  2016-05-19       Impact factor: 9.957

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