Last updated: 2023-10-30

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Knit directory: Cardiotoxicity/

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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/Knowels_trop_analysis.Rmd) and HTML (docs/Knowels_trop_analysis.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 74c2dc1 reneeisnowhere 2023-10-30 updated
Rmd d970e84 reneeisnowhere 2023-10-30 adding more analysis

library(tidyverse)
library(ggsignif)
library(cowplot)
library(ggpubr)
library(scales)
library(sjmisc)
library(kableExtra)
library(broom)
library(ComplexHeatmap)
library(ggVennDiagram)
library(biomaRt)
library(limma)
library(edgeR)

RNA-seq trial analysis

Analysis of expressed genes

RNA_seq_trial<- readRDS("data/RNA_seq_trial.RDS")

all_cpmcount <-  read_table("data/Counts_RNA_ERMatthews.txt")
cpm_count_main <- readRDS("data/cpmcount.RDS") %>% rownames_to_column(var = "ENTREZID")
colnames(cpm_count_main) <- colnames(all_cpmcount)


test_run_sample_list <- read.csv("data/test_run_sample_list.txt", row.names = 1)

colnames(RNA_seq_trial) <- c("ENTREZID",test_run_sample_list$Sample_ID)

lcpm_trial <- RNA_seq_trial %>% 
  column_to_rownames("ENTREZID") %>% 
  cpm(., log=TRUE) %>% 
  as.data.frame() #%>% 
 

row_means <- rowMeans(lcpm_trial)
x_trial <- lcpm_trial[row_means > 0,]
dim(x_trial)
[1] 13277     4
list_genes_trial <- rownames(x_trial)
ggVennDiagram::ggVennDiagram(list(list_genes_trial, cpm_count_main$ENTREZID),
                             category.names = c("Trialgenes","Maingenes"),
              show_intersect = TRUE,
              set_color = "black",
              label = "count",
              label_percent_digit = 1,
              label_size = 4,
              label_alpha = 0,
              label_color = "black",
              edge_lty = "solid", set_size = 4.5)#+

Correlation of counts files

lcpm_trial_full <- RNA_seq_trial %>% 
  column_to_rownames("ENTREZID") %>% 
  cpm(., log=TRUE) %>% 
  as.data.frame() %>% 
  rownames_to_column(var = "ENTREZID")

lcpm_trial_full %>%
  column_to_rownames(var="ENTREZID") %>%
  cor(.) %>% 
  Heatmap(.,layer_fun = function(j, i, x, y, width, height, fill) {
              grid.text(sprintf("%.3f", pindex(., i, j)), x, y, 
            gp = gpar(fontsize = 10))})

lcpm_main <- all_cpmcount %>% 
  column_to_rownames("ENTREZID") %>% 
  cpm(., log=TRUE) %>% 
  as.data.frame() %>% 
  rownames_to_column(var = "ENTREZID") %>% 
  dplyr::select(ENTREZID, all_of(starts_with("DOX"))) %>% 
  dplyr::select(ENTREZID, all_of(ends_with("3h")))  
  
combined_data <- lcpm_main %>%
  full_join(., lcpm_trial_full, by= "ENTREZID") %>% 
  column_to_rownames("ENTREZID") %>% 
  cor(.,) 


  
  Heatmap(combined_data,column_title = "Full gene list",
          layer_fun = function(j, i, x, y, width, height, fill) {
              grid.text(sprintf("%.3f", pindex(combined_data, i, j)), x, y, 
            gp = gpar(fontsize = 10))})

  only79_ind <- lcpm_main %>%
  full_join(., lcpm_trial_full, by= "ENTREZID") %>% 
    dplyr::select(ENTREZID,'3hr_0.5',"DOX.4.3h") %>% 
    column_to_rownames("ENTREZID") %>% 
  cor(.,) 

  
  Heatmap(only79_ind,column_title = "Full gene list",
          layer_fun = function(j, i, x, y, width, height, fill) {
              grid.text(sprintf("%.3f", pindex(only79_ind, i, j)), x, y, 
            gp = gpar(fontsize = 10))})

lcpm_main_veh <- all_cpmcount %>% 
  column_to_rownames("ENTREZID") %>% 
  cpm(., log=TRUE) %>% 
  as.data.frame() %>% 
  rownames_to_column(var = "ENTREZID") %>% 
  dplyr::select(ENTREZID, all_of(c(starts_with("DOX"),starts_with("VEH")))) %>% 
   dplyr::select(ENTREZID, all_of(ends_with("3h")))  
  

combined_data_veh<- lcpm_main_veh %>%
  full_join(., lcpm_trial_full, by= "ENTREZID") %>% 
  column_to_rownames("ENTREZID") %>% 
  cor(.,) 
  
  
  
  Heatmap(combined_data_veh, column_title = "all genes in list, no filtering",
          layer_fun = function(j, i, x, y, width, height, fill) {
              grid.text(sprintf("%.3f", pindex(combined_data_veh, i, j)), x, y, 
            gp = gpar(fontsize = 8))})

lcpm_trial_filter_main <- lcpm_trial_full %>% 
  filter(ENTREZID %in% cpm_count_main$ENTREZID)
 


lcpm_trial_filter_main %>% 
column_to_rownames(var="ENTREZID") %>%
  cor(.) %>% 
  Heatmap(.,column_title = "Using 14,084 expressed genes from Main data",
          layer_fun = function(j, i, x, y, width, height, fill) {
              grid.text(sprintf("%.3f", pindex(., i, j)), x, y, 
            gp = gpar(fontsize = 8))})

lcpm_trial_filter <- lcpm_trial_full %>% 
  filter(ENTREZID %in% list_genes_trial)
 

lcpm_trial_filter %>% 
column_to_rownames(var="ENTREZID") %>%
  cor(.) %>% 
  Heatmap(.,column_title = "Using 13277 expressed genes",
          layer_fun = function(j, i, x, y, width, height, fill) {
              grid.text(sprintf("%.3f", pindex(., i, j)), x, y, 
            gp = gpar(fontsize = 8))})

lcpm_main_filter_trial <- lcpm_main_veh %>% 
  filter(ENTREZID %in% list_genes_trial)

lcpm_trial_filter %>% 
  full_join(., lcpm_main_filter_trial, by = "ENTREZID") %>% 
  column_to_rownames(var="ENTREZID") %>%
  cor(.) %>% 
  Heatmap(.,column_title = "Using 13277 expressed genes",
          layer_fun = function(j, i, x, y, width, height, fill) {
              grid.text(sprintf("%.3f", pindex(., i, j)), x, y, 
            gp = gpar(fontsize = 8))})


sessionInfo()
R version 4.3.1 (2023-06-16 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/Chicago
tzcode source: internal

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] edgeR_3.42.4          limma_3.56.2          biomaRt_2.56.1       
 [4] ggVennDiagram_1.2.3   ComplexHeatmap_2.16.0 broom_1.0.5          
 [7] kableExtra_1.3.4      sjmisc_2.8.9          scales_1.2.1         
[10] ggpubr_0.6.0          cowplot_1.1.1         ggsignif_0.6.4       
[13] lubridate_1.9.3       forcats_1.0.0         stringr_1.5.0        
[16] dplyr_1.1.3           purrr_1.0.2           readr_2.1.4          
[19] tidyr_1.3.0           tibble_3.2.1          ggplot2_3.4.4        
[22] tidyverse_2.0.0       workflowr_1.7.1      

loaded via a namespace (and not attached):
  [1] RColorBrewer_1.1-3      rstudioapi_0.15.0       jsonlite_1.8.7         
  [4] shape_1.4.6             magrittr_2.0.3          magick_2.8.1           
  [7] farver_2.1.1            rmarkdown_2.25          GlobalOptions_0.1.2    
 [10] fs_1.6.3                zlibbioc_1.46.0         vctrs_0.6.4            
 [13] memoise_2.0.1           RCurl_1.98-1.12         rstatix_0.7.2          
 [16] webshot_0.5.5           htmltools_0.5.6.1       progress_1.2.2         
 [19] curl_5.1.0              sass_0.4.7              KernSmooth_2.23-22     
 [22] bslib_0.5.1             htmlwidgets_1.6.2       plotly_4.10.3          
 [25] cachem_1.0.8            whisker_0.4.1           lifecycle_1.0.3        
 [28] iterators_1.0.14        pkgconfig_2.0.3         sjlabelled_1.2.0       
 [31] R6_2.5.1                fastmap_1.1.1           GenomeInfoDbData_1.2.10
 [34] clue_0.3-65             digest_0.6.33           colorspace_2.1-0       
 [37] AnnotationDbi_1.62.2    S4Vectors_0.38.2        ps_1.7.5               
 [40] rprojroot_2.0.3         crosstalk_1.2.0         RSQLite_2.3.2          
 [43] labeling_0.4.3          filelock_1.0.2          fansi_1.0.5            
 [46] timechange_0.2.0        httr_1.4.7              abind_1.4-5            
 [49] compiler_4.3.1          proxy_0.4-27            bit64_4.0.5            
 [52] withr_2.5.1             doParallel_1.0.17       backports_1.4.1        
 [55] carData_3.0-5           DBI_1.1.3               rappdirs_0.3.3         
 [58] classInt_0.4-10         rjson_0.2.21            units_0.8-4            
 [61] tools_4.3.1             httpuv_1.6.11           glue_1.6.2             
 [64] callr_3.7.3             promises_1.2.1          sf_1.0-14              
 [67] getPass_0.2-2           cluster_2.1.4           generics_0.1.3         
 [70] gtable_0.3.4            tzdb_0.4.0              class_7.3-22           
 [73] data.table_1.14.8       hms_1.1.3               xml2_1.3.5             
 [76] car_3.1-2               utf8_1.2.3              XVector_0.40.0         
 [79] BiocGenerics_0.46.0     foreach_1.5.2           pillar_1.9.0           
 [82] yulab.utils_0.1.0       later_1.3.1             circlize_0.4.15        
 [85] lattice_0.22-5          BiocFileCache_2.8.0     bit_4.0.5              
 [88] tidyselect_1.2.0        locfit_1.5-9.8          Biostrings_2.68.1      
 [91] knitr_1.44              git2r_0.32.0            IRanges_2.34.1         
 [94] svglite_2.1.2           stats4_4.3.1            xfun_0.40              
 [97] Biobase_2.60.0          matrixStats_1.0.0       stringi_1.7.12         
[100] lazyeval_0.2.2          yaml_2.3.7              evaluate_0.22          
[103] codetools_0.2-19        RVenn_1.1.0             cli_3.6.1              
[106] systemfonts_1.0.5       munsell_0.5.0           processx_3.8.2         
[109] jquerylib_0.1.4         Rcpp_1.0.11             GenomeInfoDb_1.36.4    
[112] dbplyr_2.4.0            png_0.1-8               XML_3.99-0.14          
[115] parallel_4.3.1          ellipsis_0.3.2          blob_1.2.4             
[118] prettyunits_1.2.0       bitops_1.0-7            viridisLite_0.4.2      
[121] e1071_1.7-13            insight_0.19.6          crayon_1.5.2           
[124] GetoptLong_1.0.5        rlang_1.1.1             KEGGREST_1.40.1        
[127] rvest_1.0.3