Fig. 1

CRISPR screen analysis challenges can lead to false positives and false negatives. a QQ-plot of negative control p-values produced by Gasperini et al. (red; downsampled for visualization) and Xie et al. (gray-green). These p-values deviate substantially from the expected uniform distribution, indicating test miscalibration. b–d Technical factors, such as sequencing depth and batch, impact gRNA detection probability and observed gene expression levels in both Gasperini et al. (b) and Xie et al. (c) data. Thus, technical factors act as confounders (d), differentiating CRISPR screens from traditional differential expression applications. e Monocle2 estimates the dispersion of each gene by projecting each gene’s raw dispersion estimate onto the fitted raw dispersion-mean expression curve. This estimation procedure leads to miscalibration for high-dispersion genes