GPSAdb

GPSAdb provides a curated collection of genetic perturbation RNA-seq datasets and tools to analyze perturbed gene expression for identifying candidate causal perturbations.

Key Features:

• Manual curation: RNA-seq datasets were collected and manually curated from gene knock-out and knock-down experiments.
• Dataset composition: The resource comprises 3,048 RNA-seq datasets linked to 1,458 genes.
• Perturbation technologies: Included datasets originate from experiments using siRNA, shRNA, CRISPR/Cas9, and CRISPRi.
• Perturbed gene set generation: The database includes 6,096 perturbed gene sets derived from the curated RNA-seq data.
• Direction-specific gene sets: Perturbed gene sets are categorized into upregulated and downregulated sets separately.
• Genetic Perturbation Similarity Analysis (GPSA): GPSA integrates the perturbed gene sets to analyze differential gene expression and aid identification of candidate causal perturbations.

Scientific Applications:

• Identification of causal perturbations: Use GPSA to compare differential gene expression signatures against perturbed gene sets to nominate candidate causal perturbations.
• Gene function inference: Leverage knock-out and knock-down expression profiles to infer gene function from perturbation-induced transcriptional changes.
• Signature-driven analyses: Employ upregulated and downregulated perturbed gene sets as signatures for downstream comparative and enrichment analyses.
• Pathway and interaction discovery: Analyze perturbed expression patterns to detect affected pathways and potential genetic interactions.

Methodology:

Manual curation of RNA-seq datasets from gene knock-out/knock-down experiments; generation of perturbed gene sets and separate categorization into upregulated and downregulated sets; application of Genetic Perturbation Similarity Analysis (GPSA) to compare differential gene expression against these gene sets to identify candidate causal perturbations.