| 492 | 1 # Quick Start Guide | 
|  | 2 | 
|  | 3 Get started with COBRAxy! This guide walks you through your first metabolic analysis. | 
|  | 4 | 
|  | 5 ## Step 1: Verify Installation | 
|  | 6 | 
|  | 7 Test that COBRAxy is working: | 
|  | 8 | 
|  | 9 ```bash | 
|  | 10 # Check if tools are available | 
|  | 11 ras_generator --help | 
|  | 12 | 
|  | 13 # Should display help text without errors | 
|  | 14 ``` | 
|  | 15 | 
|  | 16 ## Step 2: Download Sample Data | 
|  | 17 | 
|  | 18 Create a sample gene expression file: | 
|  | 19 | 
|  | 20 ```bash | 
|  | 21 # Create sample data | 
|  | 22 cat > sample_expression.tsv << 'EOF' | 
|  | 23 Gene_ID	Control_1	Control_2	Treatment_1	Treatment_2 | 
|  | 24 HGNC:5	8.5	9.2	15.7	14.3 | 
|  | 25 HGNC:10	3.2	4.1	8.8	7.9 | 
|  | 26 HGNC:15	7.9	8.2	4.4	5.1 | 
|  | 27 HGNC:25	12.1	13.5	18.2	17.8 | 
|  | 28 HGNC:30	6.3	7.1	11.5	10.8 | 
|  | 29 HGNC:55	14.2	15.8	22.1	21.3 | 
|  | 30 HGNC:80	5.7	6.4	2.8	3.2 | 
|  | 31 HGNC:100	9.8	10.5	16.7	15.9 | 
|  | 32 EOF | 
|  | 33 ``` | 
|  | 34 | 
|  | 35 ## Step 3: Generate Activity Scores | 
|  | 36 | 
|  | 37 Compute Reaction Activity Scores (RAS) from your gene expression: | 
|  | 38 | 
|  | 39 ```bash | 
|  | 40 # Generate RAS scores using built-in ENGRO2 model | 
| 542 | 41 # Note: -td is optional and auto-detected after pip install | 
|  | 42 ras_generator \ | 
| 492 | 43   -in sample_expression.tsv \ | 
|  | 44   -ra ras_scores.tsv \ | 
|  | 45   -rs ENGRO2 | 
|  | 46 | 
|  | 47 # Check output | 
|  | 48 head ras_scores.tsv | 
|  | 49 ``` | 
|  | 50 | 
|  | 51 **Expected output**: | 
|  | 52 ```tsv | 
|  | 53 Reactions	Control_1	Control_2	Treatment_1	Treatment_2 | 
|  | 54 R_HEX1	8.5	9.2	15.7	14.3 | 
|  | 55 R_PGI	7.9	8.2	4.4	5.1 | 
|  | 56 ... | 
|  | 57 ``` | 
|  | 58 | 
|  | 59 ## Step 4: Create Pathway Visualizations | 
|  | 60 | 
|  | 61 Generate enriched pathway maps with statistical analysis: | 
|  | 62 | 
|  | 63 ```bash | 
|  | 64 # Create pathway maps with statistical analysis | 
| 542 | 65 # Note: -td is optional and auto-detected after pip install | 
|  | 66 marea \ | 
| 492 | 67   -using_RAS true \ | 
|  | 68   -input_data ras_scores.tsv \ | 
|  | 69   -choice_map ENGRO2 \ | 
|  | 70   -gs true \ | 
|  | 71   -idop pathway_maps | 
|  | 72 | 
|  | 73 # Check results | 
|  | 74 ls pathway_maps/ | 
|  | 75 ``` | 
|  | 76 | 
|  | 77 **Expected output**: SVG files with colored pathway maps showing metabolic changes. | 
|  | 78 | 
|  | 79 ## Step 5: View Results | 
|  | 80 | 
|  | 81 Open the generated pathway maps: | 
|  | 82 | 
|  | 83 ```bash | 
|  | 84 # Open SVG files in your browser or image viewer | 
|  | 85 # Files will be in pathway_maps/ directory | 
|  | 86 firefox pathway_maps/*.svg  # Linux | 
|  | 87 open pathway_maps/*.svg     # macOS | 
|  | 88 ``` | 
|  | 89 | 
|  | 90 ## What Just Happened? | 
|  | 91 | 
|  | 92 1. **RAS Generation**: Mapped gene expression to metabolic reactions using GPR rules | 
|  | 93 2. **Statistical Analysis**: Identified significantly altered pathways between conditions | 
|  | 94 3. **Visualization**: Created colored pathway maps highlighting metabolic changes | 
|  | 95 | 
|  | 96 ## Next Steps | 
|  | 97 | 
|  | 98 ### Learn More About the Analysis | 
|  | 99 | 
| 542 | 100 - **[Understanding RAS](/tools/ras-generator.md)** - How activity scores are computed | 
|  | 101 - **[MAREA Analysis](/tools/marea.md)** - Statistical enrichment methods | 
| 492 | 102 - **[Data Flow](getting-started.md#analysis-workflows)** - Complete workflow overview | 
|  | 103 | 
|  | 104 ### Try Advanced Features | 
|  | 105 | 
|  | 106 - **[Flux Sampling](tutorials/workflow.md#flux-simulation-workflow)** - Predict metabolic flux distributions | 
| 542 | 107 - **[Galaxy Interface](/tutorials/galaxy-setup.md)** - Web-based analysis | 
| 492 | 108 | 
|  | 109 ### Use Your Own Data | 
|  | 110 | 
| 542 | 111 - **[Data Formats](/tutorials/data-formats.md)** - Prepare your expression data | 
|  | 112 - **[Troubleshooting](/troubleshooting.md)** - Common issues and solutions | 
| 492 | 113 | 
|  | 114 ## Complete Example Pipeline | 
|  | 115 | 
|  | 116 Here's the full command sequence for reference: | 
|  | 117 | 
|  | 118 ```bash | 
|  | 119 # Set up | 
|  | 120 cd /path/to/analysis/ | 
|  | 121 | 
|  | 122 # Generate sample data (or use your own) | 
|  | 123 cat > expression.tsv << 'EOF' | 
|  | 124 [your gene expression data] | 
|  | 125 EOF | 
|  | 126 | 
|  | 127 # Run analysis pipeline | 
| 542 | 128 # Note: -td is optional and auto-detected after pip install | 
|  | 129 ras_generator -in expression.tsv -ra ras.tsv -rs ENGRO2 | 
|  | 130 marea -using_RAS true -input_data ras.tsv -choice_map ENGRO2 -gs true -idop maps | 
| 492 | 131 | 
|  | 132 # View results | 
|  | 133 ls maps/*.svg | 
|  | 134 ``` | 
|  | 135 | 
|  | 136 ## Getting Help | 
|  | 137 | 
|  | 138 If something doesn't work: | 
|  | 139 | 
|  | 140 1. **Check Prerequisites**: Ensure COBRAxy is properly installed | 
|  | 141 2. **Verify File Format**: Make sure your data is tab-separated TSV | 
|  | 142 3. **Review Logs**: Look for error messages in the terminal output | 
| 542 | 143 4. **Consult Guides**: [Troubleshooting](/troubleshooting.md) and [Installation](/installation.md) |