Biological contribution of phenotypic data on cytokine expression in the bulk RNAseq | 1,210 unique samples from DLPFC region

data_bulk <- load ("C:/Users/beker/OneDrive/Documentos/Mestrado/GitHub/Cytokines/bulk_RNAseq/bulk_DLPFC_2022.Rdata")
phenotype_dt <- pheno_DLPFC
# upload list of cytokines
file_path <- "C:/Users/beker/OneDrive/Documentos/Mestrado/GitHub/Cytokines/list_cytokines/T015/list_cytokines_T015.txt"
cytokines <- read.delim(file_path, header = TRUE, check.names = FALSE, stringsAsFactors = FALSE)
cytokines <- subset(cytokines, select = -family) # I removed the 'family' column here because it had NA values
ensembls = cytokines$ensembl

VP for cytokines

## png 
##   2
## png 
##   2
vp_df <- as.data.frame(vp)
colnames(vp_df) <- c("Cognitive decline", "Age of death", "Global AD burden", "Tangles density", "Amyloid accumulation", "Sex", "Cerebral amyloid angiopathy", "Apoe 4", "AD diagnosis", "Residuals")

# Formatando para garantir que o excel br não altere a notação científica dos valores
vp_df <- vp_df %>%
  mutate(across(where(is.numeric), ~ format(., scientific = TRUE, digits = 15)))

# Saving xlsx
write.xlsx(vp_df, file = "C:/Users/beker/OneDrive/Documentos/Mestrado/GitHub/Cytokines/bulk_RNAseq/T039/p_values_vp_bulk_T039.xlsx", rowNames = TRUE)

Session info

sessionInfo()
## R version 4.3.2 (2023-10-31 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 11 x64 (build 26100)
## 
## Matrix products: default
## 
## 
## locale:
## [1] LC_COLLATE=Portuguese_Brazil.utf8  LC_CTYPE=Portuguese_Brazil.utf8   
## [3] LC_MONETARY=Portuguese_Brazil.utf8 LC_NUMERIC=C                      
## [5] LC_TIME=Portuguese_Brazil.utf8    
## 
## time zone: America/New_York
## tzcode source: internal
## 
## attached base packages:
## [1] parallel  stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] ggrepel_0.9.5            ggbeeswarm_0.7.2         reshape2_1.4.4          
##  [4] doParallel_1.0.17        iterators_1.0.14         foreach_1.5.2           
##  [7] openxlsx_4.2.6.1         Matrix_1.6-5             ggeasy_0.1.4            
## [10] variancePartition_1.32.5 BiocParallel_1.36.0      limma_3.58.1            
## [13] ggpubr_0.6.0             lubridate_1.9.3          forcats_1.0.0           
## [16] stringr_1.5.1            dplyr_1.1.4              purrr_1.0.2             
## [19] readr_2.1.5              tidyr_1.3.1              tibble_3.2.1            
## [22] ggplot2_3.5.0            tidyverse_2.0.0         
## 
## loaded via a namespace (and not attached):
##  [1] Rdpack_2.6.1        bitops_1.0-8        rlang_1.1.3        
##  [4] magrittr_2.0.3      matrixStats_1.3.0   compiler_4.3.2     
##  [7] vctrs_0.6.5         pkgconfig_2.0.3     fastmap_1.2.0      
## [10] backports_1.4.1     labeling_0.4.3      caTools_1.18.2     
## [13] utf8_1.2.4          rmarkdown_2.27      tzdb_0.4.0         
## [16] nloptr_2.1.1        xfun_0.46           cachem_1.1.0       
## [19] jsonlite_1.8.8      EnvStats_2.8.1      highr_0.11         
## [22] remaCor_0.0.18      broom_1.0.6         R6_2.5.1           
## [25] bslib_0.8.0         stringi_1.8.3       car_3.1-2          
## [28] boot_1.3-28.1       jquerylib_0.1.4     numDeriv_2016.8-1.1
## [31] Rcpp_1.0.12         knitr_1.48          splines_4.3.2      
## [34] timechange_0.3.0    tidyselect_1.2.1    rstudioapi_0.16.0  
## [37] abind_1.4-8         yaml_2.3.10         gplots_3.1.3.1     
## [40] codetools_0.2-19    lattice_0.21-9      lmerTest_3.1-3     
## [43] plyr_1.8.9          Biobase_2.62.0      withr_3.0.1        
## [46] evaluate_0.24.0     zip_2.3.1           pillar_1.9.0       
## [49] carData_3.0-5       KernSmooth_2.23-22  generics_0.1.3     
## [52] hms_1.1.3           munsell_0.5.1       scales_1.3.0       
## [55] aod_1.3.3           minqa_1.2.7         gtools_3.9.5       
## [58] RhpcBLASctl_0.23-42 glue_1.7.0          tools_4.3.2        
## [61] fANCOVA_0.6-1       lme4_1.1-35.5       ggsignif_0.6.4     
## [64] mvtnorm_1.2-5       grid_4.3.2          rbibutils_2.2.16   
## [67] colorspace_2.1-0    nlme_3.1-163        beeswarm_0.4.0     
## [70] vipor_0.4.7         cli_3.6.2           fansi_1.0.6        
## [73] corpcor_1.6.10      gtable_0.3.5        rstatix_0.7.2      
## [76] sass_0.4.9          digest_0.6.36       BiocGenerics_0.48.1
## [79] pbkrtest_0.5.3      farver_2.1.1        htmltools_0.5.8.1  
## [82] lifecycle_1.0.4     statmod_1.5.0       MASS_7.3-60