Implement: BayesPharma and Tidymodels

## here() starts at /Users/maom/opt/BayesPharma

## Error in library(tidymodels): there is no package called 'tidymodels'

## Loading required package: brms

## Loading required package: Rcpp

## Loading 'brms' package (version 2.21.0). Useful instructions
## can be found by typing help('brms'). A more detailed introduction
## to the package is available through vignette('brms_overview').

## 
## Attaching package: 'brms'

## The following object is masked from 'package:bayesplot':
## 
##     rhat

## The following object is masked from 'package:stats':
## 
##     ar

## Loading required package: parsnip

Using BayesPharma models with Tidymodels

Tidymodels is a platform for running and analyzing models in R. This vignette demonstrates how to use the BayesPharma models with Tidy Models.

load(here::here("data", "kor_antag.rda"))
kor_antag <- kor_antag |> dplyr::transmute(
  substance_id = Drug,
  cell_id = cell_number,
  log_dose = log_dose,
  response = normalized_measurement)

Define a recipe and assign roles to different columns

kor_recipe <- kor_antag |>
  recipes::recipe() |>
  recipes::update_role(response, new_role = "outcome") |>
  recipes::update_role(log_dose, new_role = "predictor") |>
  recipes::update_role(substance_id, new_role = "predictor")

Define the model using the wrapper package for Tidymodels.

kor_model <- bayesian::bayesian(
  cores = 4,
  chains = 4,
  iter = 2000,
  control = list(adapt_delta = 0.99),
  stanvars = BayesPharma::sigmoid_stanvar(),
  init = BayesPharma::sigmoid_antagonist_init(top = 100),
  prior = BayesPharma::sigmoid_antagonist_prior(top = 100)) |>
  parsnip::set_engine("brms") |>
  parsnip::set_mode("regression") |>
  recipes::update(
    formula.override = bayesian::bayesian_formula(
      ..y ~ sigmoid(ic50, hill, top, bottom, log_dose),
      ic50 + hill + top + bottom ~ 0 + substance_id,
      nl = TRUE))

Build and run the workflow by adding the recipe and model and then running fit.

kor_workflow <- workflows::workflow() |>
  workflows::add_recipe(kor_recipe) |>
  workflows::add_model(spec = kor_model) |>
  parsnip::fit(data = kor_antag)

## Compiling Stan program...

## Trying to compile a simple C file

## Running /Library/Frameworks/R.framework/Resources/bin/R CMD SHLIB foo.c
## using C compiler: ‘Apple clang version 15.0.0 (clang-1500.3.9.4)’
## using SDK: ‘’
## clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I"/Library/Frameworks/R.framework/Versions/4.2/Resources/library/Rcpp/include/"  -I"/Library/Frameworks/R.framework/Versions/4.2/Resources/miworkspace-library/RcppEigen/include/"  -I"/Library/Frameworks/R.framework/Versions/4.2/Resources/miworkspace-library/RcppEigen/include/unsupported"  -I"/Library/Frameworks/R.framework/Versions/4.2/Resources/miworkspace-library/BH/include" -I"/Library/Frameworks/R.framework/Versions/4.2/Resources/library/StanHeaders/include/src/"  -I"/Library/Frameworks/R.framework/Versions/4.2/Resources/library/StanHeaders/include/"  -I"/Library/Frameworks/R.framework/Versions/4.2/Resources/library/RcppParallel/include/"  -I"/Library/Frameworks/R.framework/Versions/4.2/Resources/library/rstan/include" -DEIGEN_NO_DEBUG  -DBOOST_DISABLE_ASSERTS  -DBOOST_PENDING_INTEGER_LOG2_HPP  -DSTAN_THREADS  -DUSE_STANC3 -DSTRICT_R_HEADERS  -DBOOST_PHOENIX_NO_VARIADIC_EXPRESSION  -D_HAS_AUTO_PTR_ETC=0  -include '/Library/Frameworks/R.framework/Versions/4.2/Resources/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp'  -D_REENTRANT -DRCPP_PARALLEL_USE_TBB=1   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c foo.c -o foo.o
## In file included from <built-in>:1:
## In file included from /Library/Frameworks/R.framework/Versions/4.2/Resources/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:22:
## In file included from /Library/Frameworks/R.framework/Versions/4.2/Resources/miworkspace-library/RcppEigen/include/Eigen/Dense:1:
## In file included from /Library/Frameworks/R.framework/Versions/4.2/Resources/miworkspace-library/RcppEigen/include/Eigen/Core:88:
## /Library/Frameworks/R.framework/Versions/4.2/Resources/miworkspace-library/RcppEigen/include/Eigen/src/Core/util/Macros.h:628:1: error: unknown type name 'namespace'
## namespace Eigen {
## ^
## /Library/Frameworks/R.framework/Versions/4.2/Resources/miworkspace-library/RcppEigen/include/Eigen/src/Core/util/Macros.h:628:16: error: expected ';' after top level declarator
## namespace Eigen {
##                ^
##                ;
## In file included from <built-in>:1:
## In file included from /Library/Frameworks/R.framework/Versions/4.2/Resources/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:22:
## In file included from /Library/Frameworks/R.framework/Versions/4.2/Resources/miworkspace-library/RcppEigen/include/Eigen/Dense:1:
## /Library/Frameworks/R.framework/Versions/4.2/Resources/miworkspace-library/RcppEigen/include/Eigen/Core:96:10: fatal error: 'complex' file not found
## #include <complex>
##          ^~~~~~~~~
## 3 errors generated.
## make[1]: *** [foo.o] Error 1

## Start sampling

## Warning in .local(object, ...): some chains had errors; consider specifying
## chains = 1 to debug

## here are whatever error messages were returned

## [[1]]
## Stan model 'anon_model' does not contain samples.
## 
## [[2]]
## Stan model 'anon_model' does not contain samples.
## 
## [[3]]
## Stan model 'anon_model' does not contain samples.
## 
## [[4]]
## Stan model 'anon_model' does not contain samples.

kor_workflow

## ══ Workflow [trained] ════════════════════════════════════════════════════════════════════════════════════════════════════════════
## Preprocessor: Recipe
## Model: bayesian()
## 
## ── Preprocessor ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## 0 Recipe Steps
## 
## ── Model ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##  Family: gaussian 
##   Links: mu = identity; sigma = identity 
## Formula: ..y ~ sigmoid(ic50, hill, top, bottom, log_dose) 
##          ic50 ~ 0 + substance_id
##          hill ~ 0 + substance_id
##          top ~ 0 + substance_id
##          bottom ~ 0 + substance_id
##    Data: ~data (Number of observations: 73) 
## 
## The model does not contain posterior draws.

Matthew O’Meara

Using BayesPharma models with Tidymodels