Improve simulation by stemangiola · Pull Request #254 · MangiolaLaboratory/sccomp

stemangiola · 2026-01-13T01:01:37Z

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…n validation - Added support for variability formulas in the simulate_data function, allowing users to specify a formula for variability alongside the main formula. - Implemented dimension validation to ensure that simulated data does not exceed the dimensions of the original model, preventing potential errors during simulation. - Introduced a new utility function to normalize sum-to-zero vector parameters in posterior draws, addressing floating-point precision issues. - Updated Stan model to accommodate new design matrices for random effects and variability, ensuring compatibility with existing functionality. - Added comprehensive unit tests to validate the new features and ensure robustness against various model configurations.

- Introduced `sccomp_simulate` function for simulating data from fitted models, enhancing usability and flexibility. - Deprecated the `simulate_data` function, providing a warning to users to transition to `sccomp_simulate`. - Updated documentation to reflect changes and provide clear guidance on the new function's usage. - Enhanced unit tests to validate the new simulation functionality and ensure compatibility with existing workflows. - Adjusted Stan model to accommodate new parameters for user-provided coefficients, improving simulation accuracy and performance.

- Added validation to ensure user-provided coefficients sum to zero within a specified tolerance, crucial for compositional models. - Implemented checks using tidyverse to identify and report invalid coefficients, improving error handling and user feedback. - Updated comments to clarify the importance of coefficient normalization in the context of simulation.

- Added optional parameters `mean_dispersion_slope` and `mean_dispersion_intercept` to allow users to specify the slope and intercept for the mean-dispersion association, enhancing flexibility in simulations. - Updated the `simulate_data` function to reflect changes in parameter defaults, setting `variability_multiplier` to 1 for consistency. - Enhanced documentation to include new parameters and their usage, ensuring clarity for users. - Adjusted the Stan model to accommodate the new mean-dispersion parameters, improving simulation accuracy.

- Changed default `variability_multiplier` from 5 to 1 in `sccomp_simulate()` and `simulate_data()`, preserving model variability by default. - Enhanced simulation documentation for clarity on `mean_dispersion_slope` effects and updated vignette examples for consistency. - Clarified behavior of mean-dispersion association parameters in simulation, detailing their impact on intercept and factor-level variability.

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Pull request overview

This pull request improves the simulation functionality in the sccomp package by introducing a new sccomp_simulate() function with enhanced capabilities, deprecating the old simulate_data() function, and providing comprehensive documentation and tests.

Changes:

Introduced new sccomp_simulate() function with improved API design supporting separate coefficient tables, optional mean-dispersion association parameters, and better handling of new data scenarios
Changed default variability_multiplier from 5 to 1 to preserve fitted model variability by default
Added comprehensive test suite with 11 test cases covering various simulation scenarios
Updated Stan model to support user-provided coefficients and mean-dispersion parameters
Created extensive vignette with practical examples and use cases

Reviewed changes

Copilot reviewed 10 out of 10 changed files in this pull request and generated 7 comments.

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File	Description
R/simulate_data.R	Major refactoring introducing `sccomp_simulate()` with new API; deprecated `simulate_data()` wrapper
inst/stan/glm_multi_beta_binomial_simulate_data.stan	Enhanced Stan model with user-provided coefficients and mean-dispersion parameters support
tests/testthat/test-simulate_data.R	New comprehensive test suite with 407 lines covering 11 different scenarios
man/sccomp_simulate.Rd	New documentation for `sccomp_simulate()` function
man/simulate_data.Rd	Updated to indicate deprecation
dev/sccomp_simulate.qmd	New 859-line vignette with detailed examples and use cases
R/utilities.R	Added `normalize_sum_to_zero_params()` utility function (not currently used)
inst/NEWS.rd	Release notes documenting simulation improvements
NAMESPACE	Updated exports for new function
DESCRIPTION	Version bump to 2.1.25

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Copilot · 2026-01-13T01:06:39Z

+    mean_dispersion_slope = mean_dispersion_slope,
+    mean_dispersion_intercept = mean_dispersion_intercept,


The deprecated simulate_data() function references mean_dispersion_slope and mean_dispersion_intercept parameters on lines 730-731, but these parameters are not defined in the function signature. This will cause an error when users call simulate_data(). These parameters should either be added to the function signature or removed from the call to sccomp_simulate().

removed from the call to sccomp_simulate()

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

- Updated unit tests to check for the presence of the `cache_stan_model` parameter in `sccomp_simulate`, reflecting the recent function introduction. - Maintained checks for the deprecated `simulate_data` function to ensure backward compatibility. - Verified that the default value of `cache_stan_model` is set correctly across relevant functions.

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Pull request overview

Copilot reviewed 11 out of 11 changed files in this pull request and generated 8 comments.

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+  first_indices = gsub(paste0("^", param_pattern, "\\[(\\d+),.*"), "\\1", param_names)
+  second_indices = gsub(paste0("^", param_pattern, "\\[\\d+,(\\d+)\\]"), "\\1", param_names)


+    # Unique variability design (for compatibility)
+    XA = Xa %>%
+      as_tibble() %>%
      distinct()



-  matrix[A_simulated, A_simulated] XA_simulated;
-  matrix[C_simulated,M_simulated] beta_simulated;
+  matrix[N_simulated, A_simulated] Xa_simulated; // Variability design matrix for simulated data
+  matrix[A_simulated, A_simulated] XA_simulated; // Unique variability design (for compatibility with old code)


+    \item **Simulation improvements:** Changed default \code{variability_multiplier} parameter from 5 to 1 in \code{sccomp_simulate()} and \code{simulate_data()}. The new default preserves the fitted model's variability by default, rather than artificially increasing it. Users can still specify custom values greater than 1 to increase variability for benchmarking or sensitivity analysis.
+    \item Enhanced simulation documentation. Improved clarity on how \code{mean_dispersion_slope} parameter affects both intercept and factor-level variability parameters in the variability formula. Updated vignette examples to use consistent \code{number_of_draws} values.
+    \item Clarified behavior of mean-dispersion association parameters in simulation. The \code{mean_dispersion_slope} affects the slope for both intercept columns (alpha1) and factor columns (alpha2, e.g., type), with intercept only added to intercept columns as per the model specification.


 #'
 #' #     # Simulate data
-#' #     simulate_data(counts_obj, estimate, ~type, ~1, sample, cell_group, c(b_0, b_1))
+#' #     sccomp_simulate(estimate, ~type, ~1, counts_obj, sample, cell_group, c(b_0, b_1))


+# Helper function to skip tests if cmdstan is not available
+skip_cmdstan <- function() {
+  if (!instantiate::stan_cmdstan_exists()) {
+    skip("CmdStan not available")
+  }
+}
+


+\item{mean_dispersion_slope}{Optional numeric value for the slope parameter of the mean-dispersion association. If NULL, the slope from the fitted model (prec_coeff\link{2}) will be used.}
+
+\item{mean_dispersion_intercept}{Optional numeric value for the intercept parameter of the mean-dispersion association. If NULL, the intercept from the fitted model (prec_coeff\link{1}) will be used. This ensures that when only the slope is changed, the intercept remains the same.}


Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

stemangiola added 5 commits January 9, 2026 13:46

stemangiola requested a review from Copilot January 13, 2026 01:01

Copilot started reviewing on behalf of stemangiola January 13, 2026 01:02 View session

set version as 2.1.24

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stemangiola and others added 6 commits January 13, 2026 11:39

Update R/simulate_data.R

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Update DESCRIPTION

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Update man/sccomp_simulate.Rd

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Update dev/sccomp_simulate.qmd

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Merge branch 'master' into improve-simulation

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stemangiola requested a review from Copilot March 18, 2026 07:54

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Potential fix for pull request finding

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Improve simulation#254

Improve simulation#254
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		mean_dispersion_slope = mean_dispersion_slope,
		mean_dispersion_intercept = mean_dispersion_intercept,

		first_indices = gsub(paste0("^", param_pattern, "\\[(\\d+),.*"), "\\1", param_names)
		second_indices = gsub(paste0("^", param_pattern, "\\[\\d+,(\\d+)\\]"), "\\1", param_names)

		\item{mean_dispersion_slope}{Optional numeric value for the slope parameter of the mean-dispersion association. If NULL, the slope from the fitted model (prec_coeff\link{2}) will be used.}

		\item{mean_dispersion_intercept}{Optional numeric value for the intercept parameter of the mean-dispersion association. If NULL, the intercept from the fitted model (prec_coeff\link{1}) will be used. This ensures that when only the slope is changed, the intercept remains the same.}

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