Today it is possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). The main advantage of scRNA-seq is that the cellular resolution and the genome wide scope makes it possible to address issues that are intractable using other methods, e.g. bulk RNA-seq or single-cell RT-qPCR. These scRNA-seq datasets can be used to unravel heterogenous cell populations, for the discovery of new cell types and states, the reconstruction of developmental trajectories and fate decisions, all previously masked in bulk transcriptome analyses. However, to analyze scRNA-seq data, novel methods are required and some of the underlying assumptions for the methods developed for bulk RNA-seq experiments are no longer valid.