Extended Data Fig. 2: Sensitivity of DA methods to low fold change in abundance.
From: Differential abundance testing on single-cell data using k-nearest neighbor graphs
(a) True positive rate (TPR, top) and false positive rate (FPR, bottom) of DA methods calculated on cells in different bins of P(C1) used to generate condition labels (bin size = 0.05, the number on the x-axis indicates the lower value in the bin). The results for 36 simulations on 2 representative populations (colors) are shown. The filled points indicate the mean of each P(C1) bin. (b) Variability in Milo power is explained by the fraction of true positive cells close to the DA threshold for definition of ground truth. Example distributions of P(C1) for cells detected as true positives (TP) or false negatives (FN) by Milo. Examples for simulations on 2 populations (rows) and 3 simulated fold changes (columns) are shown. (c, d) True Positive Rate (TPR) of DA detection for simulated DA regions of increasing size centred at the same centroid (Erythroid2 (c) and Caudal neuroectoderm (d)). Results for 3 condition simulations per population and fold change are shown.
