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Highly Multiplexed Single-Cell RNA-seq for Defining Cell Population and Transcriptional Spaces

Jase Gehring, Jong Hwee Park, Sisi Chen, Matthew Thomson, Lior Pachter
doi: https://doi.org/10.1101/315333
Jase Gehring
Department of Molecular and Cell Biology, University of California, BerkeleyDivision of Biology and Biological Engineering, California Institute of Technology
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Jong Hwee Park
Division of Biology and Biological Engineering, California Institute of Technology
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Sisi Chen
Division of Biology and Biological Engineering, California Institute of Technology
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Matthew Thomson
Division of Biology and Biological Engineering, California Institute of Technology
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Lior Pachter
Division of Biology and Biological Engineering, California Institute of TechnologyDepartment of Computing and Mathematical Sciences, California Institute of Technology
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  • For correspondence: lpachter@caltech.edu
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Abstract

We describe a universal sample multiplexing method for single-cell RNA-seq in which cells are chemically labeled with identifying DNA oligonucleotides. Analysis of a 96-plex perturbation experiment revealed changes in cell population structure and transcriptional states that cannot be discerned from bulk measurements, establishing a cost effective means to survey cell populations from large experiments and clinical samples with the depth and resolution of single-cell RNA-seq.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 05, 2018.
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Highly Multiplexed Single-Cell RNA-seq for Defining Cell Population and Transcriptional Spaces
Jase Gehring, Jong Hwee Park, Sisi Chen, Matthew Thomson, Lior Pachter
bioRxiv 315333; doi: https://doi.org/10.1101/315333
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Highly Multiplexed Single-Cell RNA-seq for Defining Cell Population and Transcriptional Spaces
Jase Gehring, Jong Hwee Park, Sisi Chen, Matthew Thomson, Lior Pachter
bioRxiv 315333; doi: https://doi.org/10.1101/315333

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