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DroNc-Seq: Deciphering cell types in human archived brain tissues by massively-parallel single nucleus RNA-seq

Naomi Habib, Anindita Basu, Inbal Avraham-Davidi, Tyler Burks, Sourav R. Choudhury, François Aguet, Ellen Gelfand, Kristin Ardlie, David A Weitz, Orit Rozenblatt-Rosen, Feng Zhang, Aviv Regev
doi: https://doi.org/10.1101/115196
Naomi Habib
1Broad Institute of MIT and Harvard, Cambridge MA 02142
2McGovern Institute, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge MA 02140
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Anindita Basu
1Broad Institute of MIT and Harvard, Cambridge MA 02142
3John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
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Inbal Avraham-Davidi
1Broad Institute of MIT and Harvard, Cambridge MA 02142
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Tyler Burks
1Broad Institute of MIT and Harvard, Cambridge MA 02142
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Sourav R. Choudhury
1Broad Institute of MIT and Harvard, Cambridge MA 02142
2McGovern Institute, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge MA 02140
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François Aguet
1Broad Institute of MIT and Harvard, Cambridge MA 02142
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Ellen Gelfand
1Broad Institute of MIT and Harvard, Cambridge MA 02142
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Kristin Ardlie
1Broad Institute of MIT and Harvard, Cambridge MA 02142
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David A Weitz
3John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
4Department of Physics, Harvard University, Cambridge, MA 02138
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Orit Rozenblatt-Rosen
1Broad Institute of MIT and Harvard, Cambridge MA 02142
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Feng Zhang
1Broad Institute of MIT and Harvard, Cambridge MA 02142
2McGovern Institute, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge MA 02140
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  • For correspondence: zhang@broadinstitute.org aregev@broadinstitute.org
Aviv Regev
1Broad Institute of MIT and Harvard, Cambridge MA 02142
5Howard Hughes Medical Institute, Department of Biology, Koch Institute of Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge MA 02140
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  • For correspondence: zhang@broadinstitute.org aregev@broadinstitute.org
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Abstract

Single nucleus RNA-Seq (sNuc-Seq) profiles RNA from tissues that are preserved or cannot be dissociated, but does not provide the throughput required to analyse many cells from complex tissues. Here, we develop DroNc-Seq, massively parallel sNuc-Seq with droplet technology. We profile 29,543 nuclei from mouse and human archived brain samples to demonstrate sensitive, efficient and unbiased classification of cell types, paving the way for charting systematic cell atlases.

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Posted March 09, 2017.
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DroNc-Seq: Deciphering cell types in human archived brain tissues by massively-parallel single nucleus RNA-seq
Naomi Habib, Anindita Basu, Inbal Avraham-Davidi, Tyler Burks, Sourav R. Choudhury, François Aguet, Ellen Gelfand, Kristin Ardlie, David A Weitz, Orit Rozenblatt-Rosen, Feng Zhang, Aviv Regev
bioRxiv 115196; doi: https://doi.org/10.1101/115196
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DroNc-Seq: Deciphering cell types in human archived brain tissues by massively-parallel single nucleus RNA-seq
Naomi Habib, Anindita Basu, Inbal Avraham-Davidi, Tyler Burks, Sourav R. Choudhury, François Aguet, Ellen Gelfand, Kristin Ardlie, David A Weitz, Orit Rozenblatt-Rosen, Feng Zhang, Aviv Regev
bioRxiv 115196; doi: https://doi.org/10.1101/115196

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