geneRxCluster

geneRxCluster identifies and compares clusters of retroviral vector integration sites to evaluate genomic integration patterns relevant to gene therapy safety.

Key Features:

• Scan Statistics for Cluster Detection: Employs scan statistics to identify spatial differences in clustering patterns of integration sites across the genome and to compare clustering between vectors.
• False Discovery Rate Calculation: Calculates false discovery rates to assess the statistical significance of observed clusters and control for multiple testing.
• Multiple Window Widths Analysis: Implements a scan-statistic approach that compares two vectors using multiple window widths to detect clustering differentials at varying genomic scales.
• Power Evaluation with Simulated Datasets: Simulates datasets of varying sizes and signal strengths to evaluate power for cluster discovery and provide lower-bound performance estimates.

Scientific Applications:

• Gene Therapy Safety Assessment: Compare integration-site clustering across retroviral vectors to evaluate potential insertional mutagenesis risks and overall safety profiles.
• Comparative Vector Analysis: Identify genomic regions where one retroviral vector integrates more frequently than another to inform vector selection and modification.
• HIV Integration Site Analysis: Analyze experimentally determined HIV integration sites to characterize integration patterns and clustering behavior.
• Study Design and Power Estimation: Use simulation-based power evaluation to plan and optimize experimental assessments of new gene therapy vectors.

Methodology:

Uses scan statistics for spatial cluster detection, false discovery rate calculations for significance assessment, multiple window-width comparisons for multi-scale differential clustering, and simulated datasets of varying sizes and signal strengths for power evaluation.