emberwhirl-solo

I built PerturbScope, a dashboard that helps wet-lab biologists, clinician-scientists, and hybrid researchers turn large CRISPR Perturb-seq screens into reviewable target shortlists. The application combines target exploration, configurable evidence gates, matched-condition comparisons, human–mouse translation evidence, custom cell-level phenotypes, immutable provenance, and reproducible exports. I investigated how prioritization changes when reliability is evaluated before effect size. I found that strong effects can be misleading when knockdown is weak, guides disagree, donor responses fail to reproduce, coverage is limited, or translation evidence is poor. PerturbScope therefore exposes missing data, warnings, replicate structure, and analysis lineage rather than collapsing them into an opaque ranking. This matters because experimental validation is costly: transparent trust gates help researchers allocate scarce resources to candidates supported by stronger, auditable evidence while preserving scientific judgment and enabling independent review.