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9 This is a collection of GALAXY workflows illustrating different applications of the tool. 9 This is a collection of GALAXY workflows illustrating different applications of the tool.
10 The general repository is at the following link: [Galaxy workflows](http://marea4galaxy.cloud.ba.infn.it/galaxy/workflows/list_published). 10 The general repository is at the following link: [Galaxy workflows](http://marea4galaxy.cloud.ba.infn.it/galaxy/workflows/list_published).
11 11
12 To use a workflow, click the "Import" button, and it will be added to your personal workflow page. 12 To use a workflow, click the "Import" button, and it will be added to your personal workflow page.
13 13
14 | Tutorial | Description | 14 | Tutorial | Description | 🌐 Galaxy Workflow | 📘 Documentation |
15 |----------|-------------| 15 |-----------|-------------|--------------------|------------------|
16 |[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. | 16 | **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) |
17 | [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. | 17 | **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) |
18 | [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| 18 | **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) |
19 | [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. | 19 | **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) |
20 | [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 | 20 | **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) |
21 | [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 | 21 | **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) |
22 | [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. | 22 | **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) |
23 | [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. | 23
24 24
25 A more detailed description of the tools is available on the corresponding GALAXY page. 25 A more detailed description of the tools is available on the corresponding GALAXY page.
26
27 ### Flux Enrichment Analysis (Sampling Mean) — Separated Datasets
28
29 #### Goal
30 Perform a **statistical analysis of fluxes** from two different datasets derived from flux simulations using the **sampling mean** method.
31
32 #### Scenario
33 You have **one gene expression dataset per condition** (e.g., *Cancer vs Normal*).
34
35 #### 1. Import Metabolic Model
36 - Load the metabolic model.
37 - Define the **medium** and the **gene nomenclature format**.
38
39 #### 2. Expression to RAS
40 - Transform a **gene expression file** into a **RAS dataset**.
41 - This step must be applied **individually for each dataset**.
42
43 #### 3. RAS to Bounds
44 - Use the **two RAS datasets** (one per condition) as input.
45 - Generate the corresponding **flux bounds**.
46
47 #### 4. Flux Simulation
48 - Use the **output from the RAS to Bounds** step as input.
49 - Select **sampling mean (mean)** as the simulation method.
50
51 #### 5. Metabolic Flux Enrichment Analysis
52 - Create a **map of significant differences** between fluxes from the two datasets.
53 - Use the **flux simulation output** together with the **RASToBounds results** to identify enriched pathways or reactions.
54
55
56 ### Flux Clustering (Sampling Mean) + Flux Enrichment Analysis
57
58 #### Goal
59 Creation of **flux maps** from two different datasets and **clustering** based on flux simulations using the **sampling mean** method.
60
61 #### Scenario
62 You have **one gene expression dataset**.
63
64 #### 1. Import Metabolic Model
65 - Load the metabolic model.
66 - Define the **medium** and the **gene nomenclature format**.
67
68 #### 2. Expression to RAS
69 - Transform a **gene expression file** into a **RAS dataset**.
70 - This step must be applied **for each dataset**.
71
72 #### 3. RAS to Bounds
73 - Use **two different RAS datasets** as input.
74 - Generate the corresponding **flux bounds**.
75
76 #### 4. Flux Simulation
77 - Use the **output from the RAS to Bounds** step as input.
78 - Select **sampling mean (mean)** as the simulation method.
79
80 #### 5. Cluster Analysis
81 - Perform **clustering** on the **flux dataset** obtained from the simulation.
82 - Identify patterns or groups within the flux profiles.
83
84 #### 6. Metabolic Flux Enrichment Analysis
85 - Create **flux maps** showing **significant differences** between clusters.
86 - Use:
87 - The **clusters** as the *sample group specification*.
88 - The **mean of each sample** from flux sampling as the *input flux data*.
89
90
91 ### Flux Enrichment Analysis (pFBA) — Separated Datasets
92
93 #### Goal
94 Perform a **statistical analysis of fluxes** from two different datasets obtained from flux simulations using **pFBA** (parsimonious Flux Balance Analysis).
95
96 #### Scenario
97 You have **one gene expression dataset per condition** (e.g., *Cancer vs Normal*).
98
99 #### 1. Import Metabolic Model
100 - Load the metabolic model.
101 - Define the **medium** and the **gene nomenclature format**.
102
103 #### 2. Expression to RAS
104 - Transform a **gene expression file** into a **RAS dataset**.
105 - This step must be applied **individually for each dataset**.
106
107 #### 3. RAS to Bounds
108 - Use the **two RAS datasets** (one per condition) as input.
109 - Generate the corresponding **flux bounds**.
110
111 #### 4. Flux Simulation
112 - Use the **output from the RAS to Bounds** step as input.
113 - Select **pFBA** as the simulation method.
114
115 #### 5. Metabolic Flux Enrichment Analysis
116 - Perform **analysis and visualization** of **significant differences** between fluxes of the two groups (e.g., *Normal* vs *Cancer*).
117 - Use the **flux simulation output** together with the **RASToBounds results** to identify enriched or altered metabolic pathways.
118
119
120 ### Flux Clustering (pFBA) + Flux Enrichment Analysis
121
122 #### Goal
123 Perform a **statistical analysis of fluxes** from two datasets using **clusters derived from flux simulations** with **pFBA** (parsimonious Flux Balance Analysis).
124
125 #### Scenario
126 You have **two gene expression datasets**.
127
128 #### 1. Import Metabolic Model
129 - Load the metabolic model.
130 - Define the **medium** and the **gene nomenclature format**.
131
132 #### 2. Expression to RAS
133 - Transform each **gene expression file** into a **RAS dataset**.
134 - This step must be applied **for each dataset**.
135
136 #### 3. RAS to Bounds
137 - Use the **two RAS datasets** as input.
138 - Generate the corresponding **flux bounds**.
139
140 #### 4. Flux Simulation
141 - Use the **output from the RAS to Bounds** step as input.
142 - Select **pFBA** as the simulation method.
143
144 #### 5. Cluster Analysis
145 - Perform **clustering** on the **flux dataset** obtained from the pFBA simulation.
146 - Identify clusters or groups within the flux profiles.
147
148 #### 6. Metabolic Flux Enrichment Analysis
149 - Perform **analysis and visualization** of **significant differences** between fluxes of different clusters.
150 - Use:
151 - The **clusters** as the *sample group specification*.
152 - The **output from the pFBA flux simulation** as the *input flux data*.
153 - Optionally, specify **p-value** and **fold change** thresholds to refine the analysis.
154
155
156 ### RAS Clustering + Reaction Enrichment Analysis
157
158 #### Goal
159 Perform **RAS statistical analysis** using the **MaREA** tool.
160 Compare **RAS clusters** obtained from a **single gene expression dataset**.
161
162 #### Scenario
163 You have **one gene expression dataset**.
164
165 #### 1. Import Metabolic Model
166 - Load the metabolic model.
167 - Define the **medium** and the **gene nomenclature format**.
168
169 #### 2. Expression to RAS
170 - Transform the **gene expression file** into a **RAS dataset**.
171
172 #### 3. Cluster Analysis
173 - Perform **clustering** on the **RAS dataset**.
174 - Identify distinct clusters or groups within the data.
175
176 #### 4. Metabolic Reaction Enrichment Analysis (MaREA)
177 - Perform **analysis and visualization** of **significant differences** between RAS values of different clusters.
178 - Use **MaREA** to detect enriched reactions and metabolic changes.
179 - Optionally, specify **p-value** and **fold change** thresholds to refine the analysis.
180
181 ### Reaction Enrichment Analysis — Unified Datasets
182
183 #### Goal
184 Perform **RAS statistical analysis** using the **MaREA** tool.
185 Compare **groups within the same gene expression dataset**.
186
187 #### Scenario
188 You have **one gene expression dataset** along with the **corresponding class labels** (e.g., *Normal* vs *Cancer*).
189
190 #### 1. Import Metabolic Model
191 - Load the metabolic model.
192 - Define the **medium** and the **gene nomenclature format**.
193
194 #### 2. Expression to RAS
195 - Transform the **gene expression file** into a **RAS dataset**.
196
197 #### 3. Metabolic Reaction Enrichment Analysis (MaREA)
198 - Perform **analysis and visualization** of **significant differences** between RAS values of different groups (e.g., *Normal* vs *Cancer*).
199 - The **classes** are provided as input and used for **sample group specification** in the tool.
200 - Optionally, specify **p-value** and **fold change** thresholds to refine the analysis.
201
202 ### Reaction Enrichment Analysis — Separated Datasets
203
204 #### Goal
205 Perform **RAS statistical analysis** using the **MaREA** tool with **different gene expression datasets**.
206
207 #### Scenario
208 You have **one gene expression dataset per condition** (e.g., *Cancer* vs *Normal*).
209
210 #### 1. Import Metabolic Model
211 - Load the metabolic model.
212 - Define the **medium** and the **gene nomenclature format**.
213
214 #### 2. Expression to RAS
215 - Transform each **gene expression file** into a **RAS dataset**.
216 - This step must be applied **individually for each dataset**.
217
218 #### 3. Metabolic Reaction Enrichment Analysis (MaREA)
219 - Perform **analysis and visualization** of **significant differences** between RAS values from two different datasets.
220 - In this scenario, the **two RAS datasets** are provided as **separate inputs**.
221 - Optionally, specify **p-value** and **fold change** thresholds to refine the analysis.
222
26 223
27 ## Tutorial Data 224 ## Tutorial Data
28 225
29 Download example datasets used in tutorials: 226 Download example datasets used in tutorials:
30 227