Habib, NaomiAvraham-Davidi, InbalBasu, AninditaBurks, TylerShekhar, KarthikHofree, MatanChoudhury, Sourav R.Aguet, FrançoisGelfand, EllenArdlie, KristinWeitz, DavidRozenblatt-Rosen, OritZhang, FengRegev, Aviv2018-03-202017Habib, N., I. Avraham-Davidi, A. Basu, T. Burks, K. Shekhar, M. Hofree, S. R. Choudhury, et al. 2017. “Massively-parallel single nucleus RNA-seq with DroNc-seq.” Nature methods 14 (10): 955-958. doi:10.1038/nmeth.4407. http://dx.doi.org/10.1038/nmeth.4407.http://nrs.harvard.edu/urn-3:HUL.InstRepos:35015076Single 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 39,111 nuclei from mouse and human archived brain samples to demonstrate sensitive, efficient and unbiased classification of cell types, paving the way for systematic charting of cell atlases.en-USJournal Article2018-03-2010.1038/nmeth.4407