Understanding the phenotypic consequences of genetic perturbations is essential for uncovering gene function, mapping disease mechanisms, and prioritising drug targets. Despite the rapid growth of large-scale perturbation datasets, ranging from CRISPR knockouts to deep mutational scanning (MAVE) and single-cell expression profiles (Perturb-seq), their heterogeneous formats and fragmented storage across disparate repositories hinder systematic integration and meta-analysis.

We present the Perturbation Catalogue, an integrated, curated resource that harmonises human gene perturbation, variant analysis, and expression data. Central to the Catalogue is a highly unified metadata schema, implemented as an extensible Pydantic model, which standardises experimental designs, readout assays, and model systems across diverse paradigms. A robust data warehousing architecture powers a responsive, user-friendly portal and a versatile API. The platform features standardised Differential Expression Analysis (DEA) and Gene Set Enrichment Analysis (GSEA) for Perturb-seq datasets, alongside dynamic visualisations such as heatmaps for MAVE and comprehensive lists of significant hits.

By seamlessly linking different modalities of perturbation data, the Catalogue bridges the gap between target identification and functional validation.

Co-authors: Aleksandr Zakirov, Alexey Sokolov, Mallory Freeberg