Fig. 3

SCEPTRE demonstrates good calibration and sensitivity under known ground truth. a Numerical simulation comparing SCEPTRE and improved negative binomial regression on four simulated datasets. The negative binomial model was incorrectly specified on three of the four datasets. SCEPTRE maintained good calibration across all four datasets, despite model misspecification and confounder presence. b, c Application of SCEPTRE, improved negative binomial regression, Monocle regression, and Virtual FACS to pairs of negative control gRNAs and genes in b the Gasperini et al. data and c the Xie et al. data. Compared to the other methods, SCEPTRE showed good calibration. d SCEPTRE p-values for Gasperini et al. TSS-targeting controls were highly significant, and in general, more significant than the original empirical p-values. e Comparison of p-values produced by SCEPTRE for ARL15-enh to p-values produced by an arrayed, bulk RNA-seq CRISPR screen of ARL15-enh. The results of the two analyses coincided almost exactly, with both analyses rejecting gene ARL15 with high confidence after a BH correction. Dotted blue lines, rejection thresholds