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### Running command:
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###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:limpa.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings limpa_1.4.0.tar.gz
###
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* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/limpa.Rcheck’
* using R version 4.6.0 Patched (2026-04-24 r89963)
* using platform: aarch64-apple-darwin23
* R was compiled by
    Apple clang version 17.0.0 (clang-1700.3.19.1)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-05-01 00:18:37 UTC
* using option ‘--no-vignettes’
* checking for file ‘limpa/DESCRIPTION’ ... OK
* this is package ‘limpa’ version ‘1.4.0’
* checking package namespace information ... OK
* checking package dependencies ... 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 ‘limpa’ 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 ... OK
* 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 ‘limpa-Tests.R’
  Comparing ‘limpa-Tests.Rout’ to ‘limpa-Tests.Rout.save’ ...
22c22
< -3.9147383  0.7526776 
---
> -3.9147384  0.7526776 
31c31
< -3.9147383  0.7526776 
---
> -3.9147384  0.7526776 
 NOTE
* 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 NOTE
See
  ‘/Users/biocbuild/bbs-3.23-bioc/meat/limpa.Rcheck/00check.log’
for details.

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### Running command:
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###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL limpa
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* installing to library ‘/Library/Frameworks/R.framework/Versions/4.6/Resources/library’
* installing *source* package ‘limpa’ ...
** this is package ‘limpa’ version ‘1.4.0’
** 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 (limpa)

R version 4.6.0 Patched (2026-04-24 r89963) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23

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(limpa)
Loading required package: limma
> options(warnPartialMatchArgs=TRUE,warnPartialMatchAttr=TRUE,warnPartialMatchDollar=TRUE,width=120)
> 
> set.seed(0); u <- runif(100)
> 
> y.peptide <- simProteinDataSet()
> names(y.peptide)
[1] "E"       "genes"   "targets" "dpc"     "other"  
> colSums(is.na(y.peptide$E))
 S1  S2  S3  S4  S5  S6  S7  S8  S9 S10 
 35  48  43  36  44  44  38  41  35  47 
> summary(y.peptide$E[,1])
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.     NAs 
  2.160   5.548   7.025   6.711   8.586   9.717      35 
> names(y.peptide)
[1] "E"       "genes"   "targets" "dpc"     "other"  
> 
> dpcCN(y.peptide)$dpc
     beta0      beta1 
-3.9147383  0.7526776 
> dpcON(y.peptide,robust=TRUE)$dpc
    beta0     beta1 
-4.205688  0.800220 
> dpcON(y.peptide,robust=FALSE)$dpc
    beta0     beta1 
-4.205688  0.800220 
> dpc(y.peptide,model="cn")$dpc
     beta0      beta1 
-3.9147383  0.7526776 
> dpc(y.peptide,model="on")$dpc
    beta0     beta1 
-4.205688  0.800220 
> dpcfit <- dpcLegacy(y.peptide)
1 peptides are completely missing in all samples.
> dpcfit$dpc
     beta0      beta1 
-4.2061461  0.8003111 
> 
> y.protein <- dpcQuant(y.peptide,protein.id="Protein",dpcfit)
Estimating hyperparameters ...
Quantifying proteins ...
Proteins: 25  Precursors: 100 (100%)
> summary(y.protein$E[,1])
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  2.567   4.169   5.942   5.967   7.817   9.103 
> 
> Group <- factor(y.peptide$targets$Group)
> design <- model.matrix(~Group)
> fit <- dpcDE(y.protein, design, plot=FALSE)
> summary(fit$coefficients)
  (Intercept)        Group2        
 Min.   :1.856   Min.   :-1.16489  
 1st Qu.:3.678   1st Qu.:-0.18596  
 Median :5.842   Median :-0.06635  
 Mean   :5.793   Mean   : 0.05153  
 3rd Qu.:7.998   3rd Qu.: 0.26852  
 Max.   :9.422   Max.   : 1.15961  
> summary(fit$sigma)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 0.3757  0.8271  0.9731  1.0128  1.1569  2.1998 
> 
> proc.time()
   user  system elapsed 
  0.350   0.034   0.379 

R version 4.6.0 (2026-04-24 ucrt) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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(limpa)
Loading required package: limma
> options(warnPartialMatchArgs=TRUE,warnPartialMatchAttr=TRUE,warnPartialMatchDollar=TRUE,width=120)
> 
> set.seed(0); u <- runif(100)
> 
> y.peptide <- simProteinDataSet()
> names(y.peptide)
[1] "E"       "genes"   "targets" "dpc"     "other"  
> colSums(is.na(y.peptide$E))
 S1  S2  S3  S4  S5  S6  S7  S8  S9 S10 
 35  48  43  36  44  44  38  41  35  47 
> summary(y.peptide$E[,1])
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.     NAs 
  2.160   5.548   7.025   6.711   8.586   9.717      35 
> names(y.peptide)
[1] "E"       "genes"   "targets" "dpc"     "other"  
> 
> dpcCN(y.peptide)$dpc
     beta0      beta1 
-3.9147384  0.7526776 
> dpcON(y.peptide,robust=TRUE)$dpc
    beta0     beta1 
-4.205688  0.800220 
> dpcON(y.peptide,robust=FALSE)$dpc
    beta0     beta1 
-4.205688  0.800220 
> dpc(y.peptide,model="cn")$dpc
     beta0      beta1 
-3.9147384  0.7526776 
> dpc(y.peptide,model="on")$dpc
    beta0     beta1 
-4.205688  0.800220 
> dpcfit <- dpcLegacy(y.peptide)
1 peptides are completely missing in all samples.
> dpcfit$dpc
     beta0      beta1 
-4.2061461  0.8003111 
> 
> y.protein <- dpcQuant(y.peptide,protein.id="Protein",dpcfit)
Estimating hyperparameters ...
Quantifying proteins ...
Proteins: 25  Precursors: 100 (100%)
> summary(y.protein$E[,1])
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  2.567   4.169   5.942   5.967   7.817   9.103 
> 
> Group <- factor(y.peptide$targets$Group)
> design <- model.matrix(~Group)
> fit <- dpcDE(y.protein, design, plot=FALSE)
> summary(fit$coefficients)
  (Intercept)        Group2        
 Min.   :1.856   Min.   :-1.16489  
 1st Qu.:3.678   1st Qu.:-0.18596  
 Median :5.842   Median :-0.06635  
 Mean   :5.793   Mean   : 0.05153  
 3rd Qu.:7.998   3rd Qu.: 0.26852  
 Max.   :9.422   Max.   : 1.15961  
> summary(fit$sigma)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 0.3757  0.8271  0.9731  1.0128  1.1569  2.1998 
> 
> proc.time()
   user  system elapsed 
   0.53    0.09    0.65