Mercurial > repos > bimib > cobraxy
comparison COBRAxy/docs/quickstart.md @ 492:4ed95023af20 draft
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| author | francesco_lapi |
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| date | Tue, 30 Sep 2025 14:02:17 +0000 |
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| children | fcdbc81feb45 |
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| 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 | |
| 41 ras_generator -td $(pwd) \ | |
| 42 -in sample_expression.tsv \ | |
| 43 -ra ras_scores.tsv \ | |
| 44 -rs ENGRO2 | |
| 45 | |
| 46 # Check output | |
| 47 head ras_scores.tsv | |
| 48 ``` | |
| 49 | |
| 50 **Expected output**: | |
| 51 ```tsv | |
| 52 Reactions Control_1 Control_2 Treatment_1 Treatment_2 | |
| 53 R_HEX1 8.5 9.2 15.7 14.3 | |
| 54 R_PGI 7.9 8.2 4.4 5.1 | |
| 55 ... | |
| 56 ``` | |
| 57 | |
| 58 ## Step 4: Create Pathway Visualizations | |
| 59 | |
| 60 Generate enriched pathway maps with statistical analysis: | |
| 61 | |
| 62 ```bash | |
| 63 # Create pathway maps with statistical analysis | |
| 64 marea -td $(pwd) \ | |
| 65 -using_RAS true \ | |
| 66 -input_data ras_scores.tsv \ | |
| 67 -choice_map ENGRO2 \ | |
| 68 -gs true \ | |
| 69 -idop pathway_maps | |
| 70 | |
| 71 # Check results | |
| 72 ls pathway_maps/ | |
| 73 ``` | |
| 74 | |
| 75 **Expected output**: SVG files with colored pathway maps showing metabolic changes. | |
| 76 | |
| 77 ## Step 5: View Results | |
| 78 | |
| 79 Open the generated pathway maps: | |
| 80 | |
| 81 ```bash | |
| 82 # Open SVG files in your browser or image viewer | |
| 83 # Files will be in pathway_maps/ directory | |
| 84 firefox pathway_maps/*.svg # Linux | |
| 85 open pathway_maps/*.svg # macOS | |
| 86 ``` | |
| 87 | |
| 88 ## What Just Happened? | |
| 89 | |
| 90 1. **RAS Generation**: Mapped gene expression to metabolic reactions using GPR rules | |
| 91 2. **Statistical Analysis**: Identified significantly altered pathways between conditions | |
| 92 3. **Visualization**: Created colored pathway maps highlighting metabolic changes | |
| 93 | |
| 94 ## Next Steps | |
| 95 | |
| 96 ### Learn More About the Analysis | |
| 97 | |
| 98 - **[Understanding RAS](tools/ras-generator.md)** - How activity scores are computed | |
| 99 - **[MAREA Analysis](tools/marea.md)** - Statistical enrichment methods | |
| 100 - **[Data Flow](getting-started.md#analysis-workflows)** - Complete workflow overview | |
| 101 | |
| 102 ### Try Advanced Features | |
| 103 | |
| 104 - **[Flux Sampling](tutorials/workflow.md#flux-simulation-workflow)** - Predict metabolic flux distributions | |
| 105 - **[Python API](tutorials/python-api.md)** - Integrate into scripts and pipelines | |
| 106 - **[Galaxy Interface](tutorials/galaxy-setup.md)** - Web-based analysis | |
| 107 | |
| 108 ### Use Your Own Data | |
| 109 | |
| 110 - **[Data Formats](tutorials/data-formats.md)** - Prepare your expression data | |
| 111 - **[Troubleshooting](troubleshooting.md)** - Common issues and solutions | |
| 112 | |
| 113 ## Complete Example Pipeline | |
| 114 | |
| 115 Here's the full command sequence for reference: | |
| 116 | |
| 117 ```bash | |
| 118 # Set up | |
| 119 cd /path/to/analysis/ | |
| 120 | |
| 121 # Generate sample data (or use your own) | |
| 122 cat > expression.tsv << 'EOF' | |
| 123 [your gene expression data] | |
| 124 EOF | |
| 125 | |
| 126 # Run analysis pipeline | |
| 127 ras_generator -td /path/to/COBRAxy -in expression.tsv -ra ras.tsv -rs ENGRO2 | |
| 128 marea -td /path/to/COBRAxy -using_RAS true -input_data ras.tsv -choice_map ENGRO2 -gs true -idop maps | |
| 129 | |
| 130 # View results | |
| 131 ls maps/*.svg | |
| 132 ``` | |
| 133 | |
| 134 ## Getting Help | |
| 135 | |
| 136 If something doesn't work: | |
| 137 | |
| 138 1. **Check Prerequisites**: Ensure COBRAxy is properly installed | |
| 139 2. **Verify File Format**: Make sure your data is tab-separated TSV | |
| 140 3. **Review Logs**: Look for error messages in the terminal output | |
| 141 4. **Consult Guides**: [Troubleshooting](troubleshooting.md) and [Installation](installation.md) | |
| 142 | |
| 143 **Still stuck?** Ask for help in [GitHub Discussions](https://github.com/CompBtBs/COBRAxy/discussions). | |
| 144 | |
| 145 ## Summary | |
| 146 | |
| 147 🎉 **Congratulations!** You've completed your first COBRAxy analysis. You now know how to: | |
| 148 | |
| 149 - ✅ Generate metabolic activity scores from gene expression | |
| 150 - ✅ Create statistical pathway visualizations | |
| 151 - ✅ Interpret basic COBRAxy outputs | |
| 152 | |
| 153 Ready for more? Explore the [full documentation](/) to unlock COBRAxy's complete potential! |
