Mercurial > repos > bimib > cobraxy
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--- a/COBRAxy/docs/tutorials/README.md Mon Nov 03 14:49:49 2025 +0000 +++ b/COBRAxy/docs/tutorials/README.md Thu Dec 11 11:17:33 2025 +0000 @@ -11,19 +11,216 @@ To use a workflow, click the "Import" button, and it will be added to your personal workflow page. -| Tutorial | Description | -|----------|-------------| -|[Flux Enrichment Analysis - separated datasets](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=a64417ff266b740e) | Creation of maps of the fluxes differently expressed between two conditions. One gene expression dataset different for each condition. | -| [Flux Enrichment Analysis (sampling mean) - separated datasets](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=16e792953f5b45db) | Creation of maps of the fluxes differently expressed between two conditions. One gene expression dataset different for each condition. | -| [Flux clustering (sampling mean) + Flux Enrichment Analys](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=c851ab275e52f8af) | Creation of maps of the fluxes, using one dataset differently expressed for each condition and its sample group specification| -| [Flux Enrichment Analysis (pFBA) - separated datasets](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=bf0806da5b28c6d9) | Creation of maps of the fluxes differently expressed between two conditions. One gene expression dataset different for each condition. | -| [Flux clustering (pFBA) + Flux Enrichment Analysis](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=be0a27b9edd0db03) | Creation of maps of the fluxes, using one dataset differently expressed for each condition and its sample group specification | -| [RAS clustering + Reaction Enrichment Analysis](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=81991b32733a4fc4) | Creation of RAS maps, one single expression gene dataset and its sample group specification | -| [Reaction Enrichment Analysis - unified datasets](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=0d16186aaff7cbfd) |Creation of RAS maps starting from an expression dataset and its corresponding classes. One gene expression dataset as input and its classes to compare. | -| [Reaction Enrichment Analysis - separated datasets](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=290670ee50ab85f0) | Creation of RAS maps using the tool MaREA. Confrontation of two datasets that must be different from one another. | +| Tutorial | Description | 🌐 Galaxy Workflow | 📘 Documentation | +|-----------|-------------|--------------------|------------------| +| **Flux Enrichment Analysis (Sampling Mean) — Separated Datasets** | Generate flux maps highlighting differences between two conditions. | [🔗 Open](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=16e792953f5b45db) | [📄 See section](#flux-enrichment-analysis-sampling-mean--separated-datasets) | +| **Flux Clustering (Sampling Mean) + Flux Enrichment Analysis** | Cluster fluxes and identify condition-specific differences. | [🔗 Open](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=c851ab275e52f8af) | [📄 See section](#flux-clustering-sampling-mean--flux-enrichment-analysis) | +| **Flux Enrichment Analysis (pFBA) — Separated Datasets** | Compare fluxes between two conditions using pFBA simulations. | [🔗 Open](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=bf0806da5b28c6d9) | [📄 See section](#flux-enrichment-analysis-pfba--separated-datasets) | +| **Flux Clustering (pFBA) + Flux Enrichment Analysis** | Cluster pFBA-derived fluxes and analyze enriched pathways. | [🔗 Open](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=be0a27b9edd0db03) | [📄 See section](#flux-clustering-pfba--flux-enrichment-analysis) | +| **RAS Clustering + Reaction Enrichment Analysis** | Cluster RAS profiles and identify significantly enriched reactions. | [🔗 Open](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=81991b32733a4fc4) | [📄 See section](#ras-clustering--reaction-enrichment-analysis) | +| **Reaction Enrichment Analysis — Unified Datasets** | Compare RAS profiles between classes within one dataset. | [🔗 Open](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=0d16186aaff7cbfd) | [📄 See section](#reaction-enrichment-analysis--unified-datasets) | +| **Reaction Enrichment Analysis — Separated Datasets** | Analyze RAS differences between two distinct datasets. | [🔗 Open](http://marea4galaxy.cloud.ba.infn.it/galaxy/published/workflow?id=290670ee50ab85f0) | [📄 See section](#reaction-enrichment-analysis--separated-datasets) | + A more detailed description of the tools is available on the corresponding GALAXY page. +### Flux Enrichment Analysis (Sampling Mean) — Separated Datasets + +#### Goal +Perform a **statistical analysis of fluxes** from two different datasets derived from flux simulations using the **sampling mean** method. + +#### Scenario +You have **one gene expression dataset per condition** (e.g., *Cancer vs Normal*). + +#### 1. Import Metabolic Model +- Load the metabolic model. +- Define the **medium** and the **gene nomenclature format**. + +#### 2. Expression to RAS +- Transform a **gene expression file** into a **RAS dataset**. +- This step must be applied **individually for each dataset**. + +#### 3. RAS to Bounds +- Use the **two RAS datasets** (one per condition) as input. +- Generate the corresponding **flux bounds**. + +#### 4. Flux Simulation +- Use the **output from the RAS to Bounds** step as input. +- Select **sampling mean (mean)** as the simulation method. + +#### 5. Metabolic Flux Enrichment Analysis +- Create a **map of significant differences** between fluxes from the two datasets. +- Use the **flux simulation output** together with the **RASToBounds results** to identify enriched pathways or reactions. + + +### Flux Clustering (Sampling Mean) + Flux Enrichment Analysis + +#### Goal +Creation of **flux maps** from two different datasets and **clustering** based on flux simulations using the **sampling mean** method. + +#### Scenario +You have **one gene expression dataset**. + +#### 1. Import Metabolic Model +- Load the metabolic model. +- Define the **medium** and the **gene nomenclature format**. + +#### 2. Expression to RAS +- Transform a **gene expression file** into a **RAS dataset**. +- This step must be applied **for each dataset**. + +#### 3. RAS to Bounds +- Use **two different RAS datasets** as input. +- Generate the corresponding **flux bounds**. + +#### 4. Flux Simulation +- Use the **output from the RAS to Bounds** step as input. +- Select **sampling mean (mean)** as the simulation method. + +#### 5. Cluster Analysis +- Perform **clustering** on the **flux dataset** obtained from the simulation. +- Identify patterns or groups within the flux profiles. + +#### 6. Metabolic Flux Enrichment Analysis +- Create **flux maps** showing **significant differences** between clusters. +- Use: + - The **clusters** as the *sample group specification*. + - The **mean of each sample** from flux sampling as the *input flux data*. + + +### Flux Enrichment Analysis (pFBA) — Separated Datasets + +#### Goal +Perform a **statistical analysis of fluxes** from two different datasets obtained from flux simulations using **pFBA** (parsimonious Flux Balance Analysis). + +#### Scenario +You have **one gene expression dataset per condition** (e.g., *Cancer vs Normal*). + +#### 1. Import Metabolic Model +- Load the metabolic model. +- Define the **medium** and the **gene nomenclature format**. + +#### 2. Expression to RAS +- Transform a **gene expression file** into a **RAS dataset**. +- This step must be applied **individually for each dataset**. + +#### 3. RAS to Bounds +- Use the **two RAS datasets** (one per condition) as input. +- Generate the corresponding **flux bounds**. + +#### 4. Flux Simulation +- Use the **output from the RAS to Bounds** step as input. +- Select **pFBA** as the simulation method. + +#### 5. Metabolic Flux Enrichment Analysis +- Perform **analysis and visualization** of **significant differences** between fluxes of the two groups (e.g., *Normal* vs *Cancer*). +- Use the **flux simulation output** together with the **RASToBounds results** to identify enriched or altered metabolic pathways. + + +### Flux Clustering (pFBA) + Flux Enrichment Analysis + +#### Goal +Perform a **statistical analysis of fluxes** from two datasets using **clusters derived from flux simulations** with **pFBA** (parsimonious Flux Balance Analysis). + +#### Scenario +You have **two gene expression datasets**. + +#### 1. Import Metabolic Model +- Load the metabolic model. +- Define the **medium** and the **gene nomenclature format**. + +#### 2. Expression to RAS +- Transform each **gene expression file** into a **RAS dataset**. +- This step must be applied **for each dataset**. + +#### 3. RAS to Bounds +- Use the **two RAS datasets** as input. +- Generate the corresponding **flux bounds**. + +#### 4. Flux Simulation +- Use the **output from the RAS to Bounds** step as input. +- Select **pFBA** as the simulation method. + +#### 5. Cluster Analysis +- Perform **clustering** on the **flux dataset** obtained from the pFBA simulation. +- Identify clusters or groups within the flux profiles. + +#### 6. Metabolic Flux Enrichment Analysis +- Perform **analysis and visualization** of **significant differences** between fluxes of different clusters. +- Use: + - The **clusters** as the *sample group specification*. + - The **output from the pFBA flux simulation** as the *input flux data*. +- Optionally, specify **p-value** and **fold change** thresholds to refine the analysis. + + +### RAS Clustering + Reaction Enrichment Analysis + +#### Goal +Perform **RAS statistical analysis** using the **MaREA** tool. +Compare **RAS clusters** obtained from a **single gene expression dataset**. + +#### Scenario +You have **one gene expression dataset**. + +#### 1. Import Metabolic Model +- Load the metabolic model. +- Define the **medium** and the **gene nomenclature format**. + +#### 2. Expression to RAS +- Transform the **gene expression file** into a **RAS dataset**. + +#### 3. Cluster Analysis +- Perform **clustering** on the **RAS dataset**. +- Identify distinct clusters or groups within the data. + +#### 4. Metabolic Reaction Enrichment Analysis (MaREA) +- Perform **analysis and visualization** of **significant differences** between RAS values of different clusters. +- Use **MaREA** to detect enriched reactions and metabolic changes. +- Optionally, specify **p-value** and **fold change** thresholds to refine the analysis. + +### Reaction Enrichment Analysis — Unified Datasets + +#### Goal +Perform **RAS statistical analysis** using the **MaREA** tool. +Compare **groups within the same gene expression dataset**. + +#### Scenario +You have **one gene expression dataset** along with the **corresponding class labels** (e.g., *Normal* vs *Cancer*). + +#### 1. Import Metabolic Model +- Load the metabolic model. +- Define the **medium** and the **gene nomenclature format**. + +#### 2. Expression to RAS +- Transform the **gene expression file** into a **RAS dataset**. + +#### 3. Metabolic Reaction Enrichment Analysis (MaREA) +- Perform **analysis and visualization** of **significant differences** between RAS values of different groups (e.g., *Normal* vs *Cancer*). +- The **classes** are provided as input and used for **sample group specification** in the tool. +- Optionally, specify **p-value** and **fold change** thresholds to refine the analysis. + +### Reaction Enrichment Analysis — Separated Datasets + +#### Goal +Perform **RAS statistical analysis** using the **MaREA** tool with **different gene expression datasets**. + +#### Scenario +You have **one gene expression dataset per condition** (e.g., *Cancer* vs *Normal*). + +#### 1. Import Metabolic Model +- Load the metabolic model. +- Define the **medium** and the **gene nomenclature format**. + +#### 2. Expression to RAS +- Transform each **gene expression file** into a **RAS dataset**. +- This step must be applied **individually for each dataset**. + +#### 3. Metabolic Reaction Enrichment Analysis (MaREA) +- Perform **analysis and visualization** of **significant differences** between RAS values from two different datasets. +- In this scenario, the **two RAS datasets** are provided as **separate inputs**. +- Optionally, specify **p-value** and **fold change** thresholds to refine the analysis. + + ## Tutorial Data Download example datasets used in tutorials:
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id="tspan3" /></text><text - id="text35-8-2-7-2-8" - fill="#000000" - xml:space="preserve" - style="white-space:pre;display:inline" - font-family="Arial" - font-size="24px" - font-weight="bold" - letter-spacing="0em" - x="433.65015" - y="150.11345"><tspan - x="653.89612" - y="2500.4338" - id="tspan2-8-4-1-3-5">Tickness is proportional to z-score</tspan></text><g - style="clip-rule:evenodd;fill:none;fill-rule:evenodd;stroke:none;stroke-linecap:round;stroke-linejoin:round;stroke-miterlimit:1.5" - id="g42" - transform="matrix(0.86839373,0,0,0.60462766,579.67813,2475.394)"><g - id="blend" - style="isolation:isolate;mix-blend-mode:normal"><g - id="g-root-ic_imme_me7dfl1865p1f-fill" - data-item-order="1000000000" - transform="translate(3,3)" /><g - id="g-root-ic_imme_me7dfl1865p1f-stroke" - data-item-order="1000000000" - transform="translate(3,3)"><g - id="ic_imme_me7dfl1865p1f-stroke" - fill="none" - stroke-linecap="round" - stroke-linejoin="round" - stroke-miterlimit="4" - stroke="#484848" - 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--- a/COBRAxy/src/marea.py Mon Nov 03 14:49:49 2025 +0000 +++ b/COBRAxy/src/marea.py Thu Dec 11 11:17:33 2025 +0000 @@ -239,7 +239,6 @@ # (threshold_F_C - 1) / (abs(threshold_F_C) + 1) con threshold_F_C > 1 return (avg1 - avg2) / (abs(avg1) + abs(avg2)) -# TODO: I would really like for this one to get the Thanos treatment def fix_style(l :str, col :Optional[str], width :str, dash :str) -> str: """ Produces a "fixed" style string to assign to a reaction arrow in the SVG map, assigning style properties to the corresponding values passed as input params.