Last updated: 2023-06-29
Checks: 6 1
Knit directory: dgrp-starve/
This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
The command set.seed(20221101) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Using absolute paths to the files within your workflowr project makes it difficult for you and others to run your code on a different machine. Change the absolute path(s) below to the suggested relative path(s) to make your code more reproducible.
| absolute | relative |
|---|---|
| /data2/morgante_lab/nklimko/rep/dgrp-starve/ | . |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/mr.mash_f_sr.top3.Rds | snake/data/22_cov/genetic/mr.mash_f_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/multigblup_f_sr.top3.Rds | snake/data/22_cov/genetic/multigblup_f_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/multibayesC_f_sr.top3.Rds | snake/data/22_cov/genetic/multibayesC_f_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/mr.mash_f_sr.top3.Rds | snake/data/22_cov/residual/mr.mash_f_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/multigblup_f_sr.top3.Rds | snake/data/22_cov/residual/multigblup_f_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/multibayesC_f_sr.top3.Rds | snake/data/22_cov/residual/multibayesC_f_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/mr.mash_m_sr.top3.Rds | snake/data/22_cov/genetic/mr.mash_m_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/multigblup_m_sr.top3.Rds | snake/data/22_cov/genetic/multigblup_m_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/multibayesC_m_sr.top3.Rds | snake/data/22_cov/genetic/multibayesC_m_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/mr.mash_m_sr.top3.Rds | snake/data/22_cov/residual/mr.mash_m_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/multigblup_m_sr.top3.Rds | snake/data/22_cov/residual/multigblup_m_sr.top3.Rds |
| /data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/multibayesC_m_sr.top3.Rds | snake/data/22_cov/residual/multibayesC_m_sr.top3.Rds |
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 85cf149. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: code/snake/
Ignored: data/snake/
Ignored: junk/
Ignored: notes/
Untracked files:
Untracked: .snakemake/
Untracked: Rplot.pdf
Untracked: analysis/linearReg.Rmd
Untracked: bglr-f.R
Untracked: code/PCA/
Untracked: code/data-prep/
Untracked: code/fabio/
Untracked: code/gBayesC.R
Untracked: code/id_bank_creation.R
Untracked: code/intro-starve/
Untracked: code/methodComp/
Untracked: code/regress/
Untracked: colorCode
Untracked: data/bayesF.rds
Untracked: data/bayesM.rds
Untracked: data/bglr-f-130k.rds
Untracked: data/bglr-f.rds
Untracked: data/bglr-m-130k.rds
Untracked: data/bglr-m.rds
Untracked: data/corLoop-f-minus.rds
Untracked: data/corLoop-f.rds
Untracked: data/corLoop-m-Minus.rds
Untracked: data/corLoop-m-minus.rds
Untracked: data/corLoop-m.rds
Untracked: data/fRegress.txt
Untracked: data/fRegress_adj.txt
Untracked: data/fm.burglar
Untracked: data/gbayesC-f.Rds
Untracked: data/gbayesC-m.Rds
Untracked: data/gbayesC.Rds
Untracked: data/gbayes_100k-f.Rds
Untracked: data/gbayes_100k-m.Rds
Untracked: data/goGroups.txt
Untracked: data/id_bank
Untracked: data/id_bank.Rds
Untracked: data/mPart.txt
Untracked: data/mRegress.txt
Untracked: data/mRegress_adj.txt
Untracked: data/multiReg.rData
Untracked: data/pheno_f
Untracked: data/pheno_m
Untracked: data/starve-f.txt
Untracked: data/starve-m.txt
Untracked: data/xp-f.txt
Untracked: data/xp-m.txt
Untracked: data/xp_f
Untracked: data/xp_m
Untracked: data/y_save.txt
Untracked: f-cor.png
Untracked: figure/
Untracked: m-cor.png
Untracked: posterPlots.R
Untracked: runtime.png
Untracked: snake/
Unstaged changes:
Modified: .Rprofile
Modified: .gitattributes
Modified: .gitignore
Modified: README.md
Modified: _workflowr.yml
Modified: analysis/_site.yml
Modified: analysis/about.Rmd
Deleted: analysis/gremlo.R
Modified: analysis/license.Rmd
Modified: analysis/linReg.Rmd
Deleted: analysis/methodComp-f.Rmd
Deleted: analysis/methodComp-m.Rmd
Modified: analysis/methodComp.Rmd
Modified: analysis/methodPred.Rmd
Modified: analysis/multiComp.Rmd
Modified: analysis/multiReg.Rmd
Modified: analysis/pca.Rmd
Modified: analysis/predict.Rmd
Modified: analysis/recap.Rmd
Modified: analysis/rewrite.Rmd
Modified: analysis/starve.Rmd
Deleted: analysis/stepwise-f.Rmd
Deleted: analysis/stepwise-m.Rmd
Deleted: analysis/testing.R
Deleted: analysis/tips.Rmd
Modified: analysis/trace.Rmd
Modified: code/README.md
Deleted: code/baseScript-lineComp.R
Deleted: code/combineSNP.R
Deleted: code/four-comp.76979.err
Deleted: code/four-comp.76979.out
Deleted: code/four-comp.sbatch
Deleted: code/fourLinePrep.R
Deleted: code/line_avgMinus.R
Deleted: code/line_avgPlus.R
Deleted: code/line_difMinus.R
Deleted: code/line_difPlus.R
Deleted: code/snpGene.R
Deleted: code/starveDataPrep.R
Modified: data/README.md
Modified: data/avgMinus-result.txt
Modified: data/avgMinus.txt
Modified: data/avgPlus-result.txt
Modified: data/avgPlus.txt
Modified: data/difMinus-result.txt
Modified: data/difMinus.txt
Modified: data/difPlus-result.txt
Modified: data/difPlus.txt
Modified: data/geneHits.txt
Modified: data/snpList.txt
Modified: data/starve.csv
Modified: dgrp-starve.Rproj
Modified: output/README.md
Modified: output/avgMinus-result.txt
Modified: output/avgPlus-result.txt
Modified: output/difMinus-result.txt
Modified: output/difPlus-result.txt
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/covCor.Rmd) and HTML (docs/covCor.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 85cf149 | nklimko | 2023-06-29 | wflow_publish(“analysis/covCor.Rmd”) |
| html | edcc1ca | nklimko | 2023-06-29 | Build site. |
| Rmd | 36024af | nklimko | 2023-06-29 | wflow_publish(“analysis/covCor.Rmd”) |
The following methods are currently implemented:
MultiBayesC
MultiGBLUP
mr.mash
traits <- c('starvation','cafe','free.glycerol','free.glucose')
covMash <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/mr.mash_f_sr.top3.Rds")
covBlup <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/multigblup_f_sr.top3.Rds")
covBayes <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/multibayesC_f_sr.top3.Rds")
rownames(covMash) <- traits
colnames(covMash) <- traits
rownames(covBlup) <- traits
colnames(covBlup) <- traits
rownames(covBayes) <- traits
colnames(covBayes) <- traits
print("mr.mash")[1] "mr.mash"print(covMash) starvation cafe free.glycerol free.glucose
starvation 1.0000000 0.8744728 -0.8180919 -0.7278613
cafe 0.8744728 1.0000000 -0.6984191 -0.6169826
free.glycerol -0.8180919 -0.6984191 1.0000000 0.4966888
free.glucose -0.7278613 -0.6169826 0.4966888 1.0000000print("gblup")[1] "gblup"print(covBlup) starvation cafe free.glycerol free.glucose
starvation 1.0000000 -0.40194695 0.17856937 0.3449596
cafe -0.4019470 1.00000000 -0.05537373 -0.2061424
free.glycerol 0.1785694 -0.05537373 1.00000000 0.3477372
free.glucose 0.3449596 -0.20614242 0.34773718 1.0000000print("bayesC")[1] "bayesC"print(covBayes) starvation cafe free.glycerol free.glucose
starvation 1.00000000 -0.3642108 0.06414897 0.3351407
cafe -0.36421082 1.0000000 -0.10821256 -0.2337754
free.glycerol 0.06414897 -0.1082126 1.00000000 0.4240397
free.glucose 0.33514067 -0.2337754 0.42403969 1.0000000covMash <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/mr.mash_f_sr.top3.Rds")
covBlup <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/multigblup_f_sr.top3.Rds")
covBayes <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/multibayesC_f_sr.top3.Rds")
rownames(covMash) <- traits
colnames(covMash) <- traits
rownames(covBlup) <- traits
colnames(covBlup) <- traits
rownames(covBayes) <- traits
colnames(covBayes) <- traits
print("mr.mash")[1] "mr.mash"print(covMash) starvation cafe free.glycerol free.glucose
starvation 1.0000000 -0.310667600 0.259026024 0.2878386
cafe -0.3106676 1.000000000 -0.007593636 -0.1134700
free.glycerol 0.2590260 -0.007593636 1.000000000 0.3864606
free.glucose 0.2878386 -0.113470017 0.386460558 1.0000000print("gblup")[1] "gblup"print(covBlup) starvation cafe free.glycerol free.glucose
starvation 1.0000000 -0.20077482 0.32234601 0.21681177
cafe -0.2007748 1.00000000 0.02873947 -0.02419659
free.glycerol 0.3223460 0.02873947 1.00000000 0.40851429
free.glucose 0.2168118 -0.02419659 0.40851429 1.00000000print("bayesC")[1] "bayesC"print(covBayes) starvation cafe free.glycerol free.glucose
starvation 1.0000000 -0.295690713 0.361438723 0.30855544
cafe -0.2956907 1.000000000 0.007877075 -0.08569471
free.glycerol 0.3614387 0.007877075 1.000000000 0.44594467
free.glucose 0.3085554 -0.085694713 0.445944668 1.00000000covMash <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/mr.mash_m_sr.top3.Rds")
covBlup <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/multigblup_m_sr.top3.Rds")
covBayes <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/genetic/multibayesC_m_sr.top3.Rds")
rownames(covMash) <- traits
colnames(covMash) <- traits
rownames(covBlup) <- traits
colnames(covBlup) <- traits
rownames(covBayes) <- traits
colnames(covBayes) <- traits
print("mr.mash")[1] "mr.mash"print(covMash) starvation cafe free.glycerol free.glucose
starvation 1.00000000 0.3958853 -0.62460824 -0.09489319
cafe 0.39588527 1.0000000 -0.26613636 0.43982589
free.glycerol -0.62460824 -0.2661364 1.00000000 0.09257539
free.glucose -0.09489319 0.4398259 0.09257539 1.00000000print("gblup")[1] "gblup"print(covBlup) starvation cafe free.glycerol free.glucose
starvation 1.0000000 -0.40489417 0.25579581 0.34307339
cafe -0.4048942 1.00000000 0.03441261 -0.02261244
free.glycerol 0.2557958 0.03441261 1.00000000 0.45703062
free.glucose 0.3430734 -0.02261244 0.45703062 1.00000000print("bayesC")[1] "bayesC"print(covBayes) starvation cafe free.glycerol free.glucose
starvation 1.0000000 -0.302125003 0.29106739 0.294493791
cafe -0.3021250 1.000000000 -0.05066257 -0.007827465
free.glycerol 0.2910674 -0.050662570 1.00000000 0.426145604
free.glucose 0.2944938 -0.007827465 0.42614560 1.000000000covMash <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/mr.mash_m_sr.top3.Rds")
covBlup <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/multigblup_m_sr.top3.Rds")
covBayes <- readRDS("/data2/morgante_lab/nklimko/rep/dgrp-starve/snake/data/22_cov/residual/multibayesC_m_sr.top3.Rds")
rownames(covMash) <- traits
colnames(covMash) <- traits
rownames(covBlup) <- traits
colnames(covBlup) <- traits
rownames(covBayes) <- traits
colnames(covBayes) <- traits
print("mr.mash")[1] "mr.mash"print(covMash) starvation cafe free.glycerol free.glucose
starvation 1.0000000 -0.30844847 0.3383513 0.29428243
cafe -0.3084485 1.00000000 -0.0397316 -0.04264402
free.glycerol 0.3383513 -0.03973160 1.0000000 0.41443304
free.glucose 0.2942824 -0.04264402 0.4144330 1.00000000print("gblup")[1] "gblup"print(covBlup) starvation cafe free.glycerol free.glucose
starvation 1.0000000 -0.19568123 0.3980355 0.21583822
cafe -0.1956812 1.00000000 -0.1043009 -0.06051565
free.glycerol 0.3980355 -0.10430095 1.0000000 0.34762876
free.glucose 0.2158382 -0.06051565 0.3476288 1.00000000print("bayesC")[1] "bayesC"print(covBayes) starvation cafe free.glycerol free.glucose
starvation 1.0000000 -0.31518688 0.4206801 0.31394922
cafe -0.3151869 1.00000000 -0.0675322 -0.04858729
free.glycerol 0.4206801 -0.06753220 1.0000000 0.44168462
free.glucose 0.3139492 -0.04858729 0.4416846 1.00000000###FEMALE
#setwd('/data2/morgante_lab/nklimko/rep/dgrp-starve/')
bayesC <- readRDS("snake/data/20_cor/bayesC_f_starvation.Rds")
gblup <- readRDS("snake/data/20_cor/gblup_f_starvation.Rds")
multigblupData <- readRDS('snake/data/20_cor/multigblup_f_starvation.Rds')
temp <- unlist(multigblupData)
multigblup <- temp[seq(1, length(temp), by=4)]
multibayesCData <- readRDS('snake/data/20_cor/multibayesC_f_starvation.Rds')
temp <- unlist(multibayesCData)
multibayesC <- temp[seq(1, length(temp), by=4)]
mr.mashData <- readRDS('snake/data/20_cor/mr.mash_f_starvation.Rds')
temp <- unlist(mr.mashData)
mr.mash <- temp[seq(1, length(temp), by=4)]
mlassoData <- readRDS('snake/data/20_cor/mlasso_f_starvation.Rds')
temp <- unlist(mlassoData)
mlasso <- temp[seq(1, length(temp), by=4)]
topmbc <- unlist(readRDS('snake/data/20_cor/multibayesC_f_sr.top3.Rds'))
top_multibayesC <- topmbc[seq(1, length(topmbc), by=16)]
topblup <- unlist(readRDS('snake/data/20_cor/multiblup_f_sr.top3.Rds'))
top_multiblup <- topblup[seq(1, length(topblup), by=16)]
temp <- c(gblup, bayesC, multigblup, multibayesC, mr.mash, mlasso, top_multiblup, top_multibayesC)
label <- c(rep("gblup", iter), rep("bayesC", iter), rep("multigblup", iter), rep("multibayesC", iter), rep("mr.mash", iter), rep('mlasso', iter), rep('top_multiblup', iter), rep("top_multibayesC", iter))
data <- data.table(cor=as.numeric(temp), method=label)
gg[[1]] <- ggplot(data, aes(x=method, y=cor, fill=method)) +
geom_violin(color = NA, width = 0.65) +
geom_boxplot(color='#440154FF', width = 0.15) +
theme_minimal() +
stat_summary(fun=mean, color='#440154FF', geom='point',
shape=18, size=3, show.legend=FALSE) +
labs(x=NULL,y='Correlation between True and Predicted Phenotype',tag='F') +
theme(legend.position='none',
axis.text.x = element_text(angle = -45, size=10),
text=element_text(size=10),
plot.tag = element_text(size=15)) +
scale_fill_viridis(begin = 0.4, end=0.9,discrete=TRUE)
print(paste0(c('bayesC', 'gblup', 'multibayesC', 'multigblup', 'mr.mash', 'top_multibayesC', 'top_multiblup'),': ',c(mean(bayesC), mean(gblup), mean(multibayesC), mean(multigblup), mean(mr.mash), mean(top_multibayesC), mean(top_multiblup))))### MALE
#setwd('/data2/morgante_lab/nklimko/rep/dgrp-starve/')
bayesC <- readRDS("snake/data/20_cor/bayesC_m_starvation.Rds")
gblup <- readRDS("snake/data/20_cor/gblup_m_starvation.Rds")
multigblupData <- readRDS('snake/data/20_cor/multigblup_m_starvation.Rds')
temp <- unlist(multigblupData)
multigblup <- temp[seq(1, length(temp), by=4)]
multibayesCData <- readRDS('snake/data/20_cor/multibayesC_m_starvation.Rds')
temp <- unlist(multibayesCData)
multibayesC <- temp[seq(1, length(temp), by=4)]
mr.mashData <- readRDS('snake/data/20_cor/mr.mash_m_starvation.Rds')
temp <- unlist(mr.mashData)
mr.mash <- temp[seq(1, length(temp), by=4)]
mlassoData <- ('snake/data/20_cor/mlasso_m_starvation.Rds')
temp <- unlist(mlassoData)
mlasso <- temp[seq(1, length(temp), by=4)]
topmbc <- unlist(readRDS('snake/data/20_cor/multibayesC_m_sr.top3.Rds'))
top_multibayesC <- topmbc[seq(1, length(topmbc), by=16)]
topblup <- unlist(readRDS('snake/data/20_cor/multiblup_m_sr.top3.Rds'))
top_multiblup <- topblup[seq(1, length(topblup), by=16)]
temp <- c(gblup, bayesC, multigblup, multibayesC, mr.mash, mlasso, top_multiblup, top_multibayesC)
label <- c(rep("gblup", iter), rep("bayesC", iter), rep("multigblup", iter), rep("multibayesC", iter), rep("mr.mash", iter), rep('mlasso', iter), rep('top_multiblup', iter), rep("top_multibayesC", iter))
data <- data.table(cor=as.numeric(temp), method=label)
gg[[2]] <- ggplot(data, aes(x=method, y=cor, fill=method)) +
geom_violin(color = NA, width = 0.65) +
geom_boxplot(color='#440154FF', width = 0.15) +
theme_minimal() +
stat_summary(fun=mean, color='#440154FF', geom='point',
shape=18, size=3, show.legend=FALSE) +
labs(x=NULL,y='Correlation between True and Predicted Phenotype',tag='M') +
theme(legend.position='none',
axis.text.x = element_text(angle = -45, size=10),
text=element_text(size=10),
plot.tag = element_text(size=15)) +
scale_fill_viridis(begin = 0.4, end=0.9,discrete=TRUE)
print(paste0(c('bayesC', 'gblup', 'multibayesC', 'multigblup', 'mr.mash', 'top_multibayesC', 'top_multiblup'),': ',c(mean(bayesC), mean(gblup), mean(multibayesC), mean(multigblup), mean(mr.mash), mean(top_multibayesC), mean(top_multiblup))))plot_grid(gg[[1]],gg[[2]], ncol=2)
sessionInfo()R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Rocky Linux 8.5 (Green Obsidian)
Matrix products: default
BLAS/LAPACK: /opt/ohpc/pub/libs/gnu9/openblas/0.3.7/lib/libopenblasp-r0.3.7.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] lubridate_1.9.2 forcats_1.0.0 stringr_1.5.0 purrr_1.0.1
[5] readr_2.1.4 tidyr_1.3.0 tibble_3.2.1 tidyverse_2.0.0
[9] scales_1.2.1 viridis_0.6.2 viridisLite_0.4.2 doParallel_1.0.17
[13] iterators_1.0.14 foreach_1.5.2 qqman_0.1.8 cowplot_1.1.1
[17] ggplot2_3.4.2 data.table_1.14.8 dplyr_1.1.2 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.10 getPass_0.2-2 ps_1.7.2 rprojroot_2.0.3
[5] digest_0.6.31 utf8_1.2.3 R6_2.5.1 evaluate_0.20
[9] httr_1.4.5 highr_0.10 pillar_1.9.0 rlang_1.1.1
[13] rstudioapi_0.14 whisker_0.4.1 callr_3.7.3 jquerylib_0.1.4
[17] rmarkdown_2.20 munsell_0.5.0 compiler_4.1.2 httpuv_1.6.9
[21] xfun_0.37 pkgconfig_2.0.3 htmltools_0.5.4 tidyselect_1.2.0
[25] gridExtra_2.3 codetools_0.2-19 fansi_1.0.4 calibrate_1.7.7
[29] tzdb_0.3.0 withr_2.5.0 later_1.3.0 MASS_7.3-58.3
[33] grid_4.1.2 jsonlite_1.8.4 gtable_0.3.3 lifecycle_1.0.3
[37] git2r_0.31.0 magrittr_2.0.3 cli_3.6.1 stringi_1.7.12
[41] cachem_1.0.7 fs_1.6.1 promises_1.2.0.1 bslib_0.4.2
[45] generics_0.1.3 vctrs_0.6.2 tools_4.1.2 glue_1.6.2
[49] hms_1.1.3 processx_3.8.0 fastmap_1.1.1 yaml_2.3.7
[53] timechange_0.2.0 colorspace_2.1-0 knitr_1.42 sass_0.4.5