Introduction | Prerequisites | The Drug Repurposing Workflow | Case Study: COVID-19 Drug Repurposing | Step 1: Load Disease Signature | Step 2: Visualize the Signature | Step 3: Choose Filtering Strategy | Strategy A: Absolute Threshold | Strategy B: Proportional Threshold | Strategy C: Asymmetric Threshold | Step 4: Query iLINCS for Concordant Drugs | Step 5: Generate Consensus Rankings | Step 6: One-Step Convenience Function | Interpreting Results | Understanding Similarity Scores | Filtering Candidate Results | Considering Statistical Significance | Cell Line-Specific Analysis | Restricting to Relevant Cell Lines | Analyzing Cross-Cell Line Consistency | Comparing Paired vs. Unpaired Analysis | Paired Analysis | Unpaired Analysis | Comparing Results | Visualization of Results | Top Candidates Bar Plot | Similarity Distribution | Cell Line Heatmap | Working with DESeq2 Output | Working with edgeR Output | Best Practices | 1. Threshold Selection | 2. Quality Control | 3. Validation Strategy | 4. Multiple Hypothesis Testing | Advanced Filtering Scenarios | Scenario 1: Highly Specific Signature | Scenario 2: Broad Signature | Scenario 3: Direction-Specific Interest | Troubleshooting | Empty Results | Too Many Results | Summary | Next Steps | Session Information | References

Introduction | What is drugfindR? | What is LINCS? | Installation | From r-universe (Recommended) | From GitHub (Development Version) | Loading the Package | Two Approaches to Using drugfindR | 1. High-Level Convenience Functions | 2. Modular Pipeline Functions | Quick Start Example 1: Investigate a Transcriptomic Signature | Load Example Data | One-Line Analysis | Understanding the Results | Quick Start Example 2: Investigate a Specific Gene | Modular Approach: Step-by-Step Workflow | Step 1: Prepare Your Signature | Step 2: Filter by Threshold | Step 3: Query for Concordant Signatures | Step 4: Generate Consensus Rankings | Choosing Your Approach | Filtering Strategies | Absolute Thresholds | Proportional Thresholds | Direction-Specific Filtering | Understanding Library Types | Chemical Perturbagen (CP) | Gene Knockdown (KD) | Gene Overexpression (OE) | Paired vs. Unpaired Analysis | Paired Analysis (Default) | Unpaired Analysis | Common Use Cases | 1. Drug Repurposing | 2. Gene Function Discovery | 3. Mechanism of Action | Next Steps | Session Information | References

Introduction | Prerequisites | The Target Investigation Workflow | Key Questions Answered | Workflow Overview | Basic Target Investigation | Example 1: What does TP53 knockdown do? | Interpreting Results | Example 2: Which drugs mimic TP53 loss? | Example 3: Which drugs rescue TP53 loss? | Gene Overexpression Analysis | Example 4: Effects of MYC overexpression | Comparing KD vs OE | Drug Mechanism of Action | Example 5: What does metformin affect? | Example 6: Compare drug to drug | Paired vs. Unpaired Analysis | Paired Analysis (Default) | When to use paired: | Unpaired Analysis | When to use unpaired: | Cell Line Considerations | Filtering Input Cell Lines | Filtering Output Cell Lines | Cross-Cell Line Analysis | Threshold Optimization | Conservative Analysis | Liberal Analysis | Comparing Thresholds | Multiple Target Analysis | Batch Processing Targets | Pathway-Level Analysis | Analyzing Gene Sets | Visualization Strategies | Similarity Score Distribution | Top Candidates Bar Plot | Network Visualization Concept | Heatmap of Gene-Drug Relationships | Advanced Use Cases | Case 1: Synthetic Lethality Discovery | Case 2: Rescue vs. Enhancement | Case 3: Temporal Analysis | Case 4: Dose-Response Patterns | Integration with Experimental Data | Validating Predictions | Comparing with Literature | Best Practices | 1. Start Broad, Then Narrow | 2. Consider Biological Context | 3. Multiple Evidence Lines | 4. Document Parameters | Troubleshooting | No Signatures Found | Too Few Results | Summary | Next Steps | Session Information | References

Introduction | Installation | Use Cases | Package Design | Pipeline Components | Use Case 1: Identifying Candidate Drugs from an Input Signature | Step 1: Get the Signature | Step 2: Prepare the Signature | Step 3: Filter the Signature | Step 4: Get the Concordant Signatures | Step 5: Get the list of Consensus Concordant Signatures | Alternate One-Step Method | Environment Setup

Introduction | Installation | Use Cases | Package Design | Pipeline Components | Use Case 1: Identifying Candidate Drugs from an Input Signature | Step 1: Get the Signature | Step 2: Prepare the Signature | Step 3: Filter the Signature | Step 4: Get the Concordant Signatures | Step 5: Get the list of Consensus Concordant Signatures | Alternate One-Step Method | Environment Setup

Overview | Data Preparation | Identifying and Naming Pathways Clusters | Visualization | Theme Plot | Interpretation Plot | Regulation Plot | Heatmap Plot | Combined Plot | Export Results

Basics | Install KinaseTauScore | Required knowledge | Asking for help | Citing KinaseTauScore | Quick start to using to KinaseTauScore | Reproducibility | Bibliography

Intro | installation | Input | Input Format | KRSA Example | UKA Exmaple | Using the creedenzymatic package | KEA3 | PTM-SEA