@article {Macosko20151202,
	title = {Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets},
	journal = {Cell},
	volume = {161},
	number = {5},
	year = {2015},
	pages = {1202 - 1214},
	abstract = {
	Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual\&nbsp;cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell{\textquoteright}s RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts{\textquoteright} cell of origin. We analyzed\&nbsp;transcriptomes\&nbsp;from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular\&nbsp;atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq\&nbsp;will accelerate biological discovery by enabling\&nbsp;routine transcriptional profiling at single-cell resolution.

},
	issn = {0092-8674},
	doi = {http://dx.doi.org/10.1016/j.cell.2015.05.002},
	url = {http://www.sciencedirect.com/science/article/pii/S0092867415005498},
	author = {Evan~Z. Macosko and Anindita Basu and Rahul Satija and James Nemesh and Karthik Shekhar and Melissa Goldman and Itay Tirosh and Allison~R. Bialas and Nolan Kamitaki and Emily~M. Martersteck and John~J. Trombetta and David~A. Weitz and Joshua~R. Sanes and Alex~K. Shalek and Regev, Aviv and Steven~A. McCarroll}
}
