Fig. 1: Compositional data analysis in single-cell RNA-sequencing data.
From: scCODA is a Bayesian model for compositional single-cell data analysis
a Single-cell analysis of control and disease states of a human tissue sample. Disease states reflect changes in the cell-type composition. b Exemplary realization of the tested scenarios with high compositional log-fold change and low replicate number (n = 2 samples per group). Colored horizontal lines indicate statistically detected compositional changes between case and control for different methods. The error bars denote the 95% confidence interval around the mean. c The scCODA model structure with hyperparameters. Blue variables are observed. DirMult indicates a Dirichlet-Multinomial, N a Normal, logitN a Logit-Normal, and HC a Half-Cauchy distribution.
