Joint analysis of multiply perturbed cells improves statistical power and cost efficiency in Perturb-seq screens

Perturb-seq measures transcriptomic responses to genetic perturbations at scale, but standard low-MOI designs remain resource-intensive. Conventional designs aim to recover one guide RNA per cell and often discard cells carrying multiple guides during analysis. Here, we characterize how overloading cells with guides affects signal recovery, information loss, and cost reduction. Increasing guide RNA dosage eventually induced cellular stress and suppressed cell-cycle progression. Among multiplets, cells carrying two or three guides recovered perturbation responses better than higher-order guide multiplets. In a 5000-gene Perturb-seq screen across MOI levels, high MOI reduced per-cell costs by 81% while keeping information loss within 1.5-fold of a low-MOI baseline. In existing genome-wide Perturb-seq data, incorporating previously discarded multiplets increased usable cell numbers and improved statistical power. Compared with a singlet-only holdout set, adding multiplets moved signal recovery closer to the theoretical reproducibility limit. Together, these results provide an experimental and computational framework for designing cost-efficient Perturb-seq screens at scale.