SLKB

SLKB integrates and annotates synthetic lethality data from CRISPR-Cas9 combination double knockout (CDKO) experiments to support identification and analysis of synthetic lethal gene pairs across diverse cell lines.

Key Features:

• Extensive Data Integration: Integrates data from 11 CDKO experiments conducted in 22 cell lines, comprising 16,059 identified SL gene pairs and 264,424 non-SL gene pairs.
• Diverse Scoring Methods: Implements the scoring algorithms Median-B (median with background control normalization), Median-NB (median without background control normalization), sgRNA-B, sgRNA-NB, Horlbeck, GEMINI, and MAGeCK.
• Scoring Diversity Quantification: Reports that only 1.21% of the top 10% SL gene pairs overlap across the scoring methods, indicating substantial method-dependent differences.
• Visualization for Method Comparison: Provides Venn diagrams to visualize and compare SL gene pair sets and assess the impact of different scoring methods on network connectivity.
• Network Analysis: Constructs SL networks from integrated data and shows SL gene pairs are more likely to connect with other SL pairs than non-SL pairs, and that SL hub genes are more frequently shared across cell lines than individual SL gene pairs.

Scientific Applications:

• Cancer research and drug development: Supports identification of candidate synthetic lethal interactions that can be pursued as selective therapeutic targets in cancer.
• Comparative network analysis: Enables comparison of SL networks across cell lines to identify conserved SL hub genes and cell-line-specific interactions.
• Robust interpretation of CDKO screens: Facilitates prioritization of gene pairs by combining multiple scoring methods with network context.

Methodology:

Integrates CDKO datasets, computes SL scores using Median-B, Median-NB, sgRNA-B, sgRNA-NB, Horlbeck, GEMINI, and MAGeCK, generates SL networks, uses Venn diagrams for set comparison, and quantifies overlap among the top 10% SL gene pairs.