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Non-linear archetypal analysis of single-cell RNA-seq data by deep autoencoders

Fig 4

Comparisons of DEG identifications between using continuous usages and discrete group assignment.

(a) ROC AUC results for datasets simulated under NB distributions. (b) Results for datasets simulated under ZINB distributions with λ = 0.3. (c) Results for datasets simulated under ZINB distributions with λ = 0.1. (d) Results for datasets simulated under ZINB distributions with λ = 0.0. The values of ROC AUC were calculated across different signal-to-noise ratio levels. Each box and whisker plot was plotted based on ten simulated datasets. Central lines represent medians, boxes represent the interquartile range (IQR), and the upper/lower whisker represents the largest/smallest value no further than 1.5 × IQR. ROC: receiver operating characteristic; AUC: area under curve.

Fig 4

doi: https://doi.org/10.1371/journal.pcbi.1010025.g004