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Compared to bulk RNA-seq, scRNA-seq data are affected by higher noise deriving from both technical and biological factors. Technical variability mostly originates from the low amount of available mRNAs that need to be amplified in order to get the quantity suitable for sequencing. The high variability of scRNA-seq data, the presence of dropout events that leads to zero expression measurements, and the multimodality of expression of a number of transcripts, create some challenges for the detection of differentially expressed genes (DEGs), which is one of the main applications of scRNA-seq and the focus of the present work.
(Dal Molin et al., 2017) Single-Cell RNA-Sequencing: Assessment of Differential Expression Analysis Methods. Front Genet.