Figure 3.

Operational outlines of DE analytic GLM and two-class comparison approaches in scRNA-seq studies. (A) Workflow of steps for GLM-based DE approaches. (B) Workflow of steps for two-class comparison approaches. In both classes, the framework can be divided into four major parts, namely: (i) input (data provided as input to tools); (ii) pre-processing of data, this step involves data cleaning, outlier removal, normalization, etc.; (iii) model fitting and computation of DE test statistic, various distributional/model (e.g., GLM, simple statistical distribution or distribution-free) assumptions are made about the expression data, parameters of the models are estimated, and DE test statistic(s) for genes and their corresponding p-values are computed; and, (iv) assessment and interpretation of DE results.