PETRO enables robust estimation of on-target perturbation effects in Perturb-seq

Abstract

Perturb-seq uses multiple guides per target as replicates, but off-target effects can bias target-level estimates even with efficient target perturbation. We present PETRO, which recovers the on-target perturbation effect while allowing, for each outcome, an unknown minority of guides to have arbitrary off-target effects. Across CRISPRa and CRISPRi datasets, sequence-associated off-target bias persisted after pooling cells across guides and nearly doubled in one CRISPRa dataset after a published guide filter. PETRO largely removed this bias and reduced transmission of effects from independently flagged promiscuous guides. In simulations, PETRO nearly matched pooling in power without off-target effects; with off-target effects, pooling remained biased as cell numbers increased, whereas PETRO recovered the on-target perturbation effect. In cortical Perturb-seq, most ZNF219 pathway enrichments from pooling rested on one guide and did not survive majority-supported aggregation, unlike those for targets with concordant guides. PETRO enables robust target-level Perturb-seq analysis from replicate-guide agreement.