TY - JOUR T1 - ZINB-WaVE: A general and flexible method for signal extraction from single-cell RNA-seq data JF - bioRxiv DO - 10.1101/125112 SP - 125112 AU - Davide Risso AU - Fanny Perraudeau AU - Svetlana Gribkova AU - Sandrine Dudoit AU - Jean-Philippe Vert Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/04/06/125112.abstract N2 - Single-cell RNA sequencing (scRNA-seq) is a powerful technique that enables researchers to measure gene expression at the resolution of single cells. Because of the low amount of RNA present in a single cell, many genes fail to be detected even though they are expressed; these genes are usually referred to as dropouts. Here, we present a general and flexible zero-inflated negative binomial model (ZINB-WaVE), which leads to low-dimensional representations of the data that account for zero inflation (dropouts), over-dispersion, and the count nature of the data. We demonstrate, with simulations and real data, that the model and its associated estimation procedure are able to give a more stable and accurate low-dimensional representation of the data than principal component analysis (PCA) and zero-inflated factor analysis (ZIFA), without the need for a preliminary normalization step. ER -