PEtab Select

The repository for the development of the extension to PEtab for model selection, including the additional file formats and Python 3 package.

Install

The Python 3 package provides both the Python 3 and command-line (CLI) interfaces, and can be installed from PyPI, with pip3 install petab-select.

Documentation

Further documentation is available at http://petab-select.readthedocs.io/.

Examples

There are example Jupyter notebooks for usage of PEtab Select with

the command-line interface, and
the Python 3 interface,

in the doc/examples directory.

Supported features

Criterion

Methods

forward: https://en.wikipedia.org/wiki/Stepwise_regression#Main_approaches
backward: https://en.wikipedia.org/wiki/Stepwise_regression#Main_approaches
brute_force: Optimize all possible model candidates, then return the model with the best criterion value.
famos: https://doi.org/10.1371/journal.pcbi.1007230

Note that the directional methods (forward, backward) find models with the smallest step size (in terms of number of estimated parameters). For example, given the forward method and a predecessor model with 2 estimated parameters, if there are no models with 3 estimated parameters, but some models with 4 estimated parameters, then the search may return candidate models with 4 estimated parameters.

File formats

Column or key names that are surrounding by square brackets (e.g. [constraint_files]) are optional.

Selection problem

A YAML file with a description of the model selection problem.

format_version: [string]
criterion: [string]
method: [string]
model_space_files: [List of filenames]
[constraint_files]: [List of filenames]
[predecessor_model_files]: [List of filenames]

format_version: The version of the model selection extension format ( e.g. 'beta_1')
criterion: The criterion by which models should be compared (e.g. 'AIC')
method: The method by which model candidates should be generated (e.g. 'forward')
model_space_files: The filenames of model space files.
constraint_files: The filenames of constraint files.
predecessor_model_files: The filenames of predecessor (initial) model files.

Model space

A TSV with candidate models, in compressed or uncompressed format.

`model_subspace_id`	`petab_yaml`	[`sbml`]	`parameter_id_1`	...	`parameter_id_n`
(Unique) [string]	[string]	[string]	[string/float] OR [; delimited list of string/float]	...	[string/float] OR [; delimited list of string/float]

model_subspace_id: An ID for the model subspace.
petab_yaml: The PEtab YAML filename that serves as the base for a model.
sbml: An SBML filename. If the PEtab YAML file specifies multiple SBML models, this can select a specific model by model filename.
parameter_id_1...parameter_id_n : Parameter IDs that are specified to take specific values or be estimated. Example valid values are:
- uncompressed format:
  - 0.0
  - 1.0
  - estimate
- compressed format
  - 0.0;1.1;estimate (the parameter can take the values 0.0 or 1.1, or be estimated according to the PEtab problem)

Constraints

A TSV file with constraints.

`petab_yaml`	[`if`]	`constraint`
[string]	[SBML L3 Formula expression]	[SBML L3 Formula expression]

petab_yaml: The filename of the PEtab YAML file that this constraint applies to.
if: As a single YAML can relate to multiple models in the model space file, this ensures the constraint is only applied to the models that match this if statement
constraint: If a model violates this constraint, it is skipped during the model selection process and not optimized.

Model(s) (Predecessor models / model interchange / report)

Predecessor models are used to initialize an appropriate model selection method. Model IDs should be unique here and compared to model IDs in any model space files.
Model interchange refers to the format used to transfer model information between PEtab Select and a PEtab-compatible calibration tool, during the model selection process.
Report refers to the final results of the model selection process, which may include calibration results from any calibrated models, or just the select model.

Here, the format for a single model is shown. Multiple models can be specified as a YAML list of the same format.

The only required key is the PEtab YAML, as a model requires a PEtab problem. All other keys are maybe required, for the different uses of the format (e.g., the report format should include estimated_parameters), or at different stages of the model selection process (the PEtab-compatible calibration tool should provide criteria for model comparison).

[criteria]: [Dictionary of criterion names and values]
[estimated_parameters]: [Dictionary of parameter IDs and values]
[model_hash]: [string]
[model_id]: [string]
[parameters]: [Dictionary of parameter IDs and values]
petab_yaml: [string]
[predecessor_model_hash]: [string]
[sbml]: [string]

criteria: The value of the criterion by which model selection was performed, at least. Optionally, other criterion values too.
estimated_parameters: Parameter estimates, not only of parameters specified to be estimated in a model space file, but also parameters specified to be estimated in the original PEtab problem of the model.
model_hash: The model hash, generated by the PEtab Select library.
model_id: The model ID.
model_subspace_id: Same as in the model space files.
model_subspace_indices: The indices that locate this model in its model subspace.
parameters: The parameters from the problem (either values or 'estimate') (a specific combination from a model space file, but uncalibrated).
petab_yaml: Same as in model space files.
predecessor_model_hash: The hash of the model that preceded this model during the model selection process.
sbml: Same as in model space files.

Test cases

Several test cases are provided, to test the compatibility of a PEtab-compatible calibration tool with different PEtab Select features.

The test cases are available in the test_cases directory, and are provided in the model format.

Test ID	Criterion	Method	Model space files	Compressed format	Constraints files	Predecessor (initial) models files
0001	(all)	(only one model)	1
0002¹	AIC	forward	1
0003	BIC	all	1	Yes
0004	AICc	backward	1		1
0005	AIC	forward	1			1
0006	AIC	forward	1
0007²	AIC	forward	1
0008²	AICc	backward	1
0009³	AICc	FAMoS	1	Yes		Yes

1. Model M1_0 differs from M1_1 in three parameters, but only 1 additional estimated parameter. The effect of this on model selection criteria needs to be clarified. Test case 0006 is a duplicate of 0002 that doesn't have this issue.

2. Noise parameter is removed, noise is fixed to 1.

3. This is a computationally expensive problem to solve. Developers can try a model selection initialized with the provided predecessor model, which is a model start that reproducibly finds the expected model. To solve the problem reproducibly ab initio, on the order of 100 random model starts are required. This test case reproduces the model selection problem presented in https://doi.org/10.1016/j.cels.2016.01.002 .

PEtab-dev/petab_select