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### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:CyTOFpower.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings CyTOFpower_1.12.0.tar.gz
###
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* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/CyTOFpower.Rcheck’
* using R version 4.4.1 (2024-06-14)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘CyTOFpower/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘CyTOFpower’ version ‘1.12.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ...Warning: unable to access index for repository https://CRAN.R-project.org/src/contrib:
  cannot open URL 'https://CRAN.R-project.org/src/contrib/PACKAGES'
 OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘CyTOFpower’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... NOTE
Problems with news in ‘NEWS’:
  Cannot process chunk/lines:
    Changes in version 0.99.0 (2021-09-15)
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’
 ERROR
Running the tests in ‘tests/testthat.R’ failed.
Last 13 lines of output:
  2          m2        3 1.1            0.1  10          3                  3
  3          m3        3 1.0            0.1  10          3                  3
  Run the LMM model with random effect
  boundary (singular) fit: see help('isSingular')
  Run the LMM model with random effect
  boundary (singular) fit: see help('isSingular')
  [ FAIL 1 | WARN 26 | SKIP 0 | PASS 68 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Failure ('test_run_models.R:85:3'): Run the CytoGLMM - GLMM model ───────────
  `cytoglmm_res <- function_run_cytoGLMM(mock_dataset = ls_3markers$ls_mock_data)` did not throw the expected warning.
  
  [ FAIL 1 | WARN 26 | SKIP 0 | PASS 68 ]
  Error: Test failures
  Execution halted
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR, 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.20-bioc/meat/CyTOFpower.Rcheck/00check.log’
for details.

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### Running command:
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###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL CyTOFpower
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* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’
* installing *source* package ‘CyTOFpower’ ...
** using staged installation
** R
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (CyTOFpower)

R version 4.4.1 (2024-06-14) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(CyTOFpower)
> 
> test_check("CyTOFpower")
[[1]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3   1            0.1  10          3                  1

[[2]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m2        3 1.1            0.1  10          3                  1

  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3 1.0            0.1  10          3                  3
2          m2        3 1.1            0.1  10          3                  3
3          m3        3 1.0            0.1  10          3                  3
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3 1.0            0.1  10          3                  3
2          m2        3 1.1            0.1  10          3                  3
3          m3        3 1.0            0.1  10          3                  3
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3 1.0            0.1  10          3                  3
2          m2        3 1.1            0.1  10          3                  3
3          m3        3 1.0            0.1  10          3                  3
[[1]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3   1            0.1  10          3                  3

[[2]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m2        3 1.1            0.1  10          3                  3

[[3]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m3        3   1            0.1  10          3                  3

[[1]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3   1            0.1  10          3                  3

[[2]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m2        3 1.1            0.1  10          3                  3

[[3]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m3        3   1            0.1  10          3                  3

[[1]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3   1            0.1  10          3                  3

[[2]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m2        3 1.1            0.1  10          3                  3

[[3]]
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m3        3   1            0.1  10          3                  3

Joining with `by = join_by(markers)`
Joining with `by = join_by(markers)`
boundary (singular) fit: see help('isSingular')
Fitting linear models with random effects term for 'block_id'.
boundary (singular) fit: see help('isSingular')
Run the limma model with random effect
Fitting linear models with random effects term for 'block_id'.
Run the limma model with fixed effect
Run the LMM model with random effect
boundary (singular) fit: see help('isSingular')
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3 1.0            0.1  10          3                  3
2          m2        3 1.1            0.1  10          3                  3
3          m3        3 1.0            0.1  10          3                  3
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3 1.0            0.1  10          3                  3
2          m2        3 1.1            0.1  10          3                  3
3          m3        3 1.0            0.1  10          3                  3
Run the limma model with random effect
Fitting linear models with random effects term for 'block_id'.
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3 1.0            0.1  10          3                  3
2          m2        3 1.1            0.1  10          3                  3
3          m3        3 1.0            0.1  10          3                  3
Run the limma model with fixed effect
  marker_name nb_donor rho subject_effect mu0 dispersion nb_cell_per_sample
1          m1        3 1.0            0.1  10          3                  3
2          m2        3 1.1            0.1  10          3                  3
3          m3        3 1.0            0.1  10          3                  3
Run the LMM model with random effect
boundary (singular) fit: see help('isSingular')
Run the LMM model with random effect
boundary (singular) fit: see help('isSingular')
[ FAIL 1 | WARN 26 | SKIP 0 | PASS 68 ]

══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test_run_models.R:85:3'): Run the CytoGLMM - GLMM model ───────────
`cytoglmm_res <- function_run_cytoGLMM(mock_dataset = ls_3markers$ls_mock_data)` did not throw the expected warning.

[ FAIL 1 | WARN 26 | SKIP 0 | PASS 68 ]
Error: Test failures
Execution halted