Clean up the environment

rm(list = ls())

Load library

library(readxl)       # For reading Excel files
library(ggpubr)       # For creating publication-ready plots
library(dplyr)        # For data manipulation

Load required libraries for data reading, plotting, and data manipulation

# Targeted MS data
PP.targeted.serum <- read_excel("Data/Data.xlsx", sheet = "PP_serum_MS")
# Pig info and postprandial metadata
PigInfo <- read_excel("Data/Data.xlsx", sheet = "PigInfo")
PP_metadata <- read_excel("Data/Data.xlsx", sheet = "PP_metadata")

Data organization

PP_Feed.intake <- PP_metadata %>% select(PigID, PPfeedIntake.g)
# Calculate tryptophan intake (in mg) for each pig based on their diet
Trp.intake <- PP_metadata %>% inner_join(PigInfo, by = "PigID") %>%
                  mutate(Trp_intake = if_else(Diet == "ALAC", PPfeedIntake.g * 1.03, PPfeedIntake.g * 0.89)) %>% # Calculate tryptophan intake based on the assigned diet
                  select(PigID, Trp_intake)

Figure

# Filter data for the 120-minute time point, join with tryptophan intake data, and create scatter plot
Fig <- PP.targeted.serum %>% inner_join(PigInfo, by = "PigID") %>%
          filter(TimePoint == "120 min") %>%
          select(PigID, Diet, Tryptophan) %>%
          inner_join(Trp.intake, by = "PigID") %>%
          ggscatter(x = "Tryptophan", y = "Trp_intake", 
                    xlab = "Serum tryptophan at 120 min post-meal (uM)", ylab = "Tryptophan intake from formula (mg)",
                    palette = c("turquoise3","purple"), add = "reg.line") + stat_cor(method = "pearson", label.x = 120) 


# Save the figure as a pdf file
ggsave(plot=Fig, height=5, width=5.5, dpi=300, filename="Figure 2/Fig2G.pdf", useDingbats=FALSE)


Fig

sessionInfo()
## R version 4.2.2 (2022-10-31)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur ... 10.16
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] dplyr_1.1.3   ggpubr_0.6.0  ggplot2_3.5.1 readxl_1.4.3 
## 
## loaded via a namespace (and not attached):
##  [1] tidyselect_1.2.0  xfun_0.40         bslib_0.5.1       purrr_1.0.2      
##  [5] splines_4.2.2     lattice_0.20-45   carData_3.0-5     colorspace_2.1-0 
##  [9] vctrs_0.6.5       generics_0.1.3    htmltools_0.5.6.1 yaml_2.3.7       
## [13] mgcv_1.8-41       utf8_1.2.4        rlang_1.1.2       jquerylib_0.1.4  
## [17] pillar_1.9.0      glue_1.6.2        withr_3.0.1       lifecycle_1.0.4  
## [21] munsell_0.5.1     ggsignif_0.6.4    gtable_0.3.5      cellranger_1.1.0 
## [25] ragg_1.2.6        evaluate_1.0.1    labeling_0.4.3    knitr_1.45       
## [29] fastmap_1.1.1     fansi_1.0.6       highr_0.10        broom_1.0.5      
## [33] scales_1.3.0      backports_1.4.1   cachem_1.0.8      jsonlite_1.8.8   
## [37] abind_1.4-5       farver_2.1.1      systemfonts_1.0.5 textshaping_0.3.7
## [41] digest_0.6.33     rstatix_0.7.2     grid_4.2.2        cli_3.6.2        
## [45] tools_4.2.2       magrittr_2.0.3    sass_0.4.7        tibble_3.2.1     
## [49] tidyr_1.3.0       car_3.1-2         pkgconfig_2.0.3   Matrix_1.5-4.1   
## [53] rmarkdown_2.28    rstudioapi_0.15.0 R6_2.5.1          nlme_3.1-163     
## [57] compiler_4.2.2