Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets

TL;DR: This comprehensive analysis of tissue-specific regulatory elements, transcription factor binding, and gene expression programs in three regions of the human visual system reveals features of regulatory element evolution that shape tissue- specific gene expression Programs and defines regulatory elements with the potential to contribute to Mendelian and complex disorders of human vision.

TL;DR: It is proposed that NMF is a desirable method to analyze heterogeneous single-cell RNA-Seq data and it is discovered that in conjugation with the modularity detection method FEM, NMF reveals meaningful protein-protein interaction modules.

TL;DR: This work presents scRNASeqDB, a database that includes almost all the currently available human single cell transcriptome datasets (n = 38) covering 200 human cell lines or cell types and 13,440 samples.

TL;DR: It is shown that P2ry1-Pet1 DR neurons – the most molecularly distinct subtype – possess unique efferent projections and electrophysiological properties, and these data complement and extend previous DR characterizations.

TL;DR: In this paper, a density-based notion of clusters is proposed to discover clusters of arbitrary shape, which can be used for class identification in large spatial databases and is shown to be more efficient than the well-known algorithm CLAR-ANS.

TL;DR: DBSCAN, a new clustering algorithm relying on a density-based notion of clusters which is designed to discover clusters of arbitrary shape, is presented which requires only one input parameter and supports the user in determining an appropriate value for it.

TL;DR: Seurat is a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns, and correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups.

TL;DR: A single-cell digital gene expression profiling assay with only a single mouse blastomere is described, which detected the expression of 75% more genes than microarray techniques and identified 1,753 previously unknown splice junctions called by at least 5 reads.