Host factor prioritization for pan-viral genetic perturbation screens using random intercept models and network propagation
Fig 3
Stability analysis on simulated and biological data.
We assessed the stability of our random effects model using the Jaccard index and Spearman’s correlation coefficient (y-axis) given the first i ∈ {10, 25, 50, 75, 100} highest ranked genes from 100 bootstrap samples (x-axis). (a) For low error variance σ2 = 1, gene rankings are highly stable. While increasing the error variance keeps correlations stable, Jaccard indexes reduce. The network diffusion is stable against increasing error variances having similar Jaccard indexes and correlation for medium and high error variance. (b) On the biological data set increasing the number of viruses does not significantly reduce Jaccard indexes or correlations for the random effects, with the exception for the correlations for 10 genes. The network diffusion has stable Jaccard indexes for increasing virus numbers at around 60%. The correlations between bootstrap samples, however, decrease with a higher number of viruses.