synlet

synlet processes and analyzes high-throughput synthetic lethal RNAi (siRNA) screen data in R to identify genes exhibiting synthetic lethality for applications in cancer research and drug discovery.

Key Features:

• Complete Analytical Pipeline: Provides end-to-end processing and analysis of synthetic lethal RNAi screen data within the R environment.
• Quality Control Metrics: Computes quality control metrics including the Z' factor to assess screen reliability and reproducibility.
• Data Normalization Techniques: Implements normalization methods including B-score and fraction of control or sample normalization to adjust for systematic variability.
• Visualization Tools: Generates visualization outputs to explore and interpret screen data and results.
• Hit Selection Algorithms: Implements multiple hit-selection algorithms to identify high-confidence synthetic lethal candidate genes from screen data.

Scientific Applications:

• Cancer Research: Identification of synthetic lethal interactions and candidate genes to study cancer vulnerabilities.
• Drug Discovery: Prioritization of therapeutic targets by identifying genes whose knockdown confers synthetic lethality for potential drug development.

Methodology:

Implements quality control using Z' factor, normalization using B-score and fraction of control/sample methods, visualization routines, and multiple statistical hit-selection algorithms.