| 492 | 1 # Getting Started | 
|  | 2 | 
|  | 3 Welcome to COBRAxy! This guide will help you get up and running with metabolic flux analysis. | 
|  | 4 | 
|  | 5 ## What is COBRAxy? | 
|  | 6 | 
|  | 7 COBRAxy is a comprehensive toolkit for metabolic flux analysis that bridges the gap between omics data and biological insights. It provides: | 
|  | 8 | 
|  | 9 - **Data Integration**: Combine gene expression and metabolite data | 
|  | 10 - **Metabolic Modeling**: Use constraint-based models for flux analysis | 
|  | 11 - **Visualization**: Generate interactive pathway maps | 
|  | 12 - **Statistical Analysis**: Perform enrichment and sensitivity analysis | 
|  | 13 | 
|  | 14 ## Core Concepts | 
|  | 15 | 
|  | 16 ### Reaction Activity Scores (RAS) | 
|  | 17 RAS quantify how active metabolic reactions are based on gene expression data. COBRAxy computes RAS by: | 
|  | 18 1. Mapping genes to reactions via GPR (Gene-Protein-Reaction) rules | 
|  | 19 2. Applying logical operations (AND/OR) based on enzyme complexes | 
|  | 20 3. Producing activity scores for each reaction in each sample | 
|  | 21 | 
|  | 22 ### Reaction Propensity Scores (RPS) | 
|  | 23 RPS indicate metabolic preferences based on metabolite abundance: | 
|  | 24 1. Map metabolites to reactions as substrates/products | 
|  | 25 2. Weight by stoichiometry and frequency | 
|  | 26 3. Compute propensity scores using log-normalized formulas | 
|  | 27 | 
|  | 28 ### Flux Sampling | 
|  | 29 Sample feasible flux distributions using: | 
|  | 30 - **CBS (Coordinate Hit-and-Run with Rounding)**: Fast, uniform sampling | 
|  | 31 - **OptGP (Optimal Growth Parallel)**: Growth-optimized sampling | 
|  | 32 | 
|  | 33 ## Analysis Workflows | 
|  | 34 | 
|  | 35 COBRAxy supports two main analysis paths: | 
|  | 36 | 
|  | 37 ### 1. Enrichment Analysis Workflow | 
|  | 38 ```bash | 
|  | 39 # Generate activity scores | 
|  | 40 ras_generator → RAS values | 
|  | 41 rps_generator → RPS values | 
|  | 42 | 
|  | 43 # Statistical enrichment analysis | 
|  | 44 marea → Enriched pathway maps | 
|  | 45 ``` | 
|  | 46 | 
|  | 47 **Use when**: You want to identify significantly altered pathways and create publication-ready maps. | 
|  | 48 | 
|  | 49 ### 2. Flux Simulation Workflow | 
|  | 50 ```bash | 
|  | 51 # Apply constraints to model | 
|  | 52 ras_generator → RAS values | 
|  | 53 ras_to_bounds → Constrained model | 
|  | 54 | 
|  | 55 # Sample flux distributions | 
|  | 56 flux_simulation → Flux samples | 
|  | 57 flux_to_map → Final visualizations | 
|  | 58 ``` | 
|  | 59 | 
|  | 60 **Use when**: You want to predict metabolic flux distributions and study network-wide changes. | 
|  | 61 | 
|  | 62 ## Your First Analysis | 
|  | 63 | 
|  | 64 Let's run a basic analysis with sample data: | 
|  | 65 | 
|  | 66 ### Step 1: Prepare Your Data | 
|  | 67 | 
|  | 68 You'll need: | 
|  | 69 - **Gene expression data**: TSV file with genes (rows) × samples (columns) | 
|  | 70 - **Metabolic model**: SBML file or use built-in models (ENGRO2, Recon) | 
|  | 71 - **Metabolite data** (optional): TSV file with metabolites (rows) × samples (columns) | 
|  | 72 | 
|  | 73 ### Step 2: Generate Activity Scores | 
|  | 74 | 
|  | 75 ```bash | 
|  | 76 # Generate RAS from expression data | 
| 542 | 77 ras_generator \ | 
| 492 | 78   -in expression_data.tsv \ | 
|  | 79   -ra ras_output.tsv \ | 
|  | 80   -rs ENGRO2 | 
|  | 81 ``` | 
|  | 82 | 
|  | 83 ### Step 3: Create Pathway Maps | 
|  | 84 | 
|  | 85 ```bash | 
|  | 86 # Generate enriched pathway maps | 
| 542 | 87 marea \ | 
| 492 | 88   -using_RAS true \ | 
|  | 89   -input_data ras_output.tsv \ | 
|  | 90   -choice_map ENGRO2 \ | 
|  | 91   -gs true \ | 
|  | 92   -idop pathway_maps | 
|  | 93 ``` | 
|  | 94 | 
|  | 95 ### Step 4: View Results | 
|  | 96 | 
|  | 97 Your analysis will generate: | 
|  | 98 - **RAS values**: `ras_output.tsv` - Activity scores for each reaction | 
|  | 99 - **Statistical maps**: `pathway_maps/` - SVG files with enrichment visualization | 
|  | 100 - **Log files**: Detailed execution logs for troubleshooting | 
|  | 101 | 
|  | 102 ## Built-in Models | 
|  | 103 | 
|  | 104 COBRAxy includes ready-to-use metabolic models: | 
|  | 105 | 
|  | 106 | Model | Organism | Reactions | Genes | Description | | 
|  | 107 |-------|----------|-----------|-------|-------------| | 
|  | 108 | **ENGRO2** | Human | ~2,000 | ~500 | Focused human metabolism model | | 
|  | 109 | **Recon** | Human | ~10,000 | ~2,000 | Comprehensive human metabolism | | 
|  | 110 | 
| 542 | 111 Models are stored in the `src/local/` directory and include: | 
| 492 | 112 - SBML files | 
|  | 113 - GPR rules | 
|  | 114 - Gene mapping tables | 
|  | 115 - Pathway templates | 
|  | 116 | 
|  | 117 ## Data Formats | 
|  | 118 | 
|  | 119 ### Gene Expression Format | 
|  | 120 ```tsv | 
|  | 121 Gene_ID	Sample_1	Sample_2	Sample_3 | 
|  | 122 HGNC:5	12.5	8.3	15.7 | 
|  | 123 HGNC:10	3.2	4.1	2.8 | 
|  | 124 HGNC:15	7.9	11.2	6.4 | 
|  | 125 ``` | 
|  | 126 | 
|  | 127 ### Metabolite Format | 
|  | 128 ```tsv | 
|  | 129 Metabolite_ID	Sample_1	Sample_2	Sample_3 | 
|  | 130 glucose	100.5	85.3	120.7 | 
|  | 131 pyruvate	45.2	38.1	52.8 | 
|  | 132 lactate	23.9	41.2	19.4 | 
|  | 133 ``` | 
|  | 134 | 
|  | 135 ## Next Steps | 
|  | 136 | 
|  | 137 Now that you understand the basics: | 
|  | 138 | 
| 547 | 139 1. **[Quick Start Guide](quickstart)** - Complete walkthrough with example data | 
|  | 140 2. **[Galaxy Tutorial](tutorials/galaxy-setup)** - Web-based analysis setup | 
| 542 | 141 3. **[Tools Reference](/tools/)** - Detailed documentation for each tool | 
| 492 | 142 | 
|  | 143 ## Need Help? | 
|  | 144 | 
| 547 | 145 - **[Troubleshooting](troubleshooting)** - Common issues and solutions | 
| 492 | 146 - **[GitHub Issues](https://github.com/CompBtBs/COBRAxy/issues)** - Report bugs or ask questions | 
| 547 | 147 - **[Contributing](contributing)** - Help improve COBRAxy |