Nature MethodsGenomicsPeer-reviewed journal article
DroNc-Seq: Deciphering cell types in human archived brain tissues by massively-parallel single nucleus RNA-seq
Naomi HabibiD, Inbal Avraham‐DavidiiD, Anindita BasuiD, Tyler BurksiD, Karthik ShekhariD, Matan HofreeiD, Sourav ChoudhuryiD, François AguetiD, Ellen Gelfand, Kristin ArdlieiD, David A. WeitziD, Orit Rozenblatt–RoseniD, Feng ZhangiD, Aviv RegeviD
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.
- organism: mouse
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- approach: experimental assay
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