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About MOST

Overview

• Sorting Tables
• Formula Bar
• Renaming Metabolites
• Renaming Compartments
• Visualization Overview

Installing MOST

• Requirements
• Windows
• Known Issues
• Linux
• Macintosh

File Menu

• Load SBML
• Load CSV
• Metabolites Column Selector
• Reactions Column Selector
• Add Metabolite Prompt
• Load Excel Spreadsheets
• Load from Model Collection
• Saving Files
• Save
• Save As SBML
• Save As CSV
• Clear Tables
• Exit

Analysis Menu

• FBA
• GDBB
• E-Flux2
• SPOT

Visualization Menu

• Visualize Compartment
• Show Visualization Report
• Locate Identifier Columns
• Set Edge Flux Levels
• Reset Edge Flux Levels to Default
• Visualization Frame Menus
• Save As SVG
• Save As PNG
• Find

Edit Menu

• Unused Metabolites
• Suspicious Metabolites
• Undo/Redo
• Find/Replace
• Select All
• Add Row/Column
• Unsort

Options Menu

• Select Solvers
• Set Solver Parameters
• Visualization Options
• Graph All in Database
• Scale Edge Thickness
• Ignore Water for Reaction Matching
• Show Visualization Report

Toolbar

• Save
• Copy/Paste
• Undo/Redo
• Find/Replace

Context Menus

• Table Menus
• Select Row(s)/Column(s)/Cell(s)
• Select All
• Copy/Paste
• Clear Contents
• Delete Row(s)
• Highlight Participating Reactions
• Un-Highlight Participating Reactions
• Reaction Editor
• Table Header Menus
• Delete Column
• Formula Bar Menu
• Console Menu
• Console Popout
• Tree Menu

Keyboard Shortcuts

• List of Keyboard Shortcuts

SPOT (Simplified Pearson cOrrelation
with Transcriptomic data) Tutorial

Step 1

Load Model. To load an SBML or CSV model, go to File, then click either Load SBML or Load CSV. A model from the Model Collection Database can also be used. Select File → Load from Model Collection Database (Alt+F then Alt+D). If necessary, the model can be edited after being loaded depending on your experiment. For a test purpose, select ecoli_core_model, then click the OK button on the Model Collection dialog. This model will be used for this tutorial.

The progress bar will appear while the model is loading, then close when the load is finished.

Note: SPOT does not require a Biological Objective to be set.

Step 2

Load Gene Expression File.

SPOT requires a CSV file with two columns where the first column in the gene name and the second column is the gene expression as shown below:

Click here to download a sample gene expression csv file that can be used for the test of the ecoli_core_model.

Step 3

Run Analysis. Select Analysis → SPOT (Alt+A then Alt+S)..

A file browser will appear. Select the gene expression csv downloaded in Step 2, then click the Open button on the file browser.

A progress bar will appear:

After SPOT is finished, a new link of the optimization result will be added to the tree on the upper right panel, and results will be displayed in the console. The numerical values in the Flux Value column shows the predicted metabolic fluxes.