TY - JOUR T1 - Fast and accurate single-cell RNA-Seq analysis by clustering of transcript-compatibility counts JF - bioRxiv DO - 10.1101/036863 SP - 036863 AU - Vasilis Ntranos AU - Govinda M. Kamath AU - Jesse Zhang AU - Lior Pachter AU - David N. Tse Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/03/04/036863.abstract N2 - Current approaches to single-cell transcriptomic analysis are computationally intensive and require assay-specific modeling which limit their scope and generality. We propose a novel method that departs from standard analysis pipelines, comparing and clustering cells based not on their transcript or gene quantifications but on their transcript-compatibility read counts. In re-analysis of two landmark yet disparate single-cell RNA-Seq datasets, we show that our method is up to two orders of magnitude faster than previous approaches, provides accurate and in some cases improved results, and is directly applicable to data from a wide variety of assays. ER -