Overview of the site
Usage of this App
This tab contains explanations of the different functions available through PSAMM and instructions on how to perform them on this site.
Import Models in PSAMM
This tab contains functions to convert model files to other formats such as YAML, SBML, JSON, Excel, and Table.
Run Analysis Functions in PSAMM
This tab contains 16 analysis functions from PSAMM. There is an option to upload your own YAML model or use the default model already installed. The user can select a function from a drop down menu upon which optional arguments will appear for that specific function.
PSAMM is an open source software that is designed for the curation and analysis of metabolic models. It supports model version tracking, model annotation, data integration, data parsing and formatting, consistency checking, automatic gap filling, and model simulations.
The PSAMM main page can be found at https://zhanglab.github.io/psamm/ and the PSAMM tutorial can be found at https://psamm.readthedocs.io/en/stable/index.html
The following figure is the overview workflow in PSAMM:
This App Includes Import and Export Functions and Sixteen Analysis Functions
Import Functions:
Convert SBML or JSON format metabolic models to YAML format
An Ecoli Core Model in SBML format is already uploaded as a default and will be used in the import conversion if no user input file is given
Export Functions:
Convert YAML format metabolic models to SBML, Excel, or Table formats
Analysis Functions:
masscheck:
Check whether the model is mass consistent.
chargecheck:
Check whether compound charge is balanced in a reaction. Balanced reactions are those reactions where the total charge is consistent on the left and right side of the reaction equation. Reactions that are not balanced will be printed out.
formulacheck:
Check whether reactions in the model are elementally balanced. Balanced reactions are those reactions where the number of elements (atoms) is consistent on the left and right side of the reaction equation. Reactions that are not balanced will be printed out.
duplicatescheck:
Check for duplicated reactions in the model. This command reports any reactions in the model that appear more than once. Stoichiometry and reaction directionality is by default disregarded when checking for duplicates but can be enabled using the options.
fluxcheck:
Check that reactions are flux consistent in a model. A reaction is flux consistent if there exists any steady-state flux solution where the flux of the given reaction is non-zero.
gapcheck:
Check for compound production gaps in model.
fba:
Run flux balance analysis on the model.
fva:
Run flux variablity analysis on the model.
gapfill:
Run the GapFill algorithms on the model
fastgapfill:
Run the FastGapFill gap-filling algorithm on model
primarypairs:
Predict primary pairs of reactions. This command is used to predict element-transferring reactant/product pairs in the reactions of the model. This can be used to determine the flow of elements through reactions.
fluxcoupling:
Find flux coupled reactions in the model. This identifies any reaction pairs where the flux of one reaction constrains the flux of another reaction. The reactions can be coupled in three distinct ways depending on the ratio between the reaction fluxes. The reactions can be fully coupled (the ratio is static and non-zero); partially coupled (the ratio is bounded and non-zero); or directionally coupled (the ratio is non-zero).
genedelete:
Find reactions requiring a specified gene and delete them from model. Reports the new objective flux after the gene was deleted.
robustness:
Run robustness analysis on the model. Given a reaction to maximize and a reaction to vary, the robustness analysis will run FBA while fixing the reaction to vary at each iteration. The reaction will be fixed at the specified number of steps between the minimum and maximum flux value specified in the model.
randomsparse:
Find a random minimal network of model reactions. Given a reaction to optimize and a threshold, delete reactions randomly until the flux of the reaction to optimize falls under the threshold. Keep deleting reactions until no more reactions can be deleted. By default this uses standard FBA (not tFBA). Since the internal fluxes are irrelevant the FBA and tFBA are equivalent for this purpose.
search:
Search for reactions and compounds in the model.
Usage Notes:
1. In order to run fba and fva successfully, the objective reaction (biomass reaction) needs to be specified
2. If the charges or formulas of compounds are not defined in the model, then chargecheck or formulacheck can not output reliable results.
3. The threshold for the randomsparse function can be specified as an absolute flux (e.g. '1.23') or a relative flux of the full model flux (e.g. '40.5%')
4. Any optional text file inputs should be formatted so that every object in the file is listed on its own line
5. Some functions have default values put in if there is no user input. The default values are stated above the optional argument inputs.
Model Upload Instructions:
When uploading your own model in the 'Run analysis functions in PSAMM' tab, the uploaded model file should define the reactions, compounds and medium (exchange.yaml) used in the model.
Be sure to select all files that are listed in the model file to be uploaded at once. The model file should look like the following:
In the model file example above, the '<PATH>' should be absolute path that locates to other files included in the model
PSAMM requires YAML formatted metabolic model as input for further analysis.
This format allows for a human readable representation of the model components and
allows for enhanced customization with respect to the organization of the metabolic
model, thus is more accessible for both modeler and experimental biologists. Here PSAMM
provides several functions to convert popular model formats to YAML format. Please load the model
upload before downloading results.
Import Model
Convert other formats of metabolic model (e.g. SBML, JSON) to YAML format
Download Import Results
Download YAML modelExport Model
Convert model from YAML format to SBML, Excel, tsv, or csv file format