Fig. 4: Addressing confounding factors in scRNA-seq.
From: Single-cell RNA sequencing technologies and bioinformatics pipelines
a Technical batch effects are a well-known problem in scRNA-seq when the experiment (condition) is conducted in different plates (environment). Cell-specific scaling factors, such as capture and RT efficiency, dropout/amplification bias, dilution factor, and sequencing amount, must be considered in the normalization step. b Single-cell latent variable model (scLVM) can effectively remove the variation explained by the cell-cycle effect. The clear separation is lost in scLVM-corrected expression data using PCA (visualization adapted from ref. 59). c The expression value y can be modeled as a linear combination of r technical and biological factors and k latent factors with a noise matrix
