Last updated: 2023-09-27

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Knit directory: Cardiotoxicity/

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library(car)
library(tidyverse)
library(BiocGenerics)
library(data.table)
library(cowplot)
library(ggsignif)
library(RColorBrewer)
library(broom)
library(limma)
library(corrplot)
library(ggVennDiagram)
library(ComplexHeatmap)
library(gridtext)
library(paletteer)
toplistall <- readRDS("data/toplistall.RDS")
siglist <- readRDS("data/siglist_final.RDS")
list2env(siglist, envir = .GlobalEnv)
<environment: R_GlobalEnv>
cpmcounts <- readRDS("data/cpmcount.RDS")

Figure 4: Gene expression responses to AC treatments converge over time.

A. Pearson correlation of drug response in pairwise analysis

efit2 <- readRDS("data/efit2_final.RDS")
FCmatrix <- subset(efit2$coefficients)

colnames(FCmatrix) <-
  c(
    "DNR\n3h",
    "DOX\n3h",
    "EPI\n3h",
    "MTX\n3h",
    "TRZ\n3h",
    "DNR\n24h",
    "DOX\n24h",
    "EPI\n24h",
    "MTX\n24h",
    "TRZ\n24h"
  )


mat_col <-
  data.frame(
    time = c(rep("3 hours", 5), rep("24 hours", 5)),
    class = (c(
      "AC", "AC", "AC", "nAC", "nAC", "AC", "AC", "AC", "nAC", "nAC"
    )),
    TOP2i = c(rep("yes", 4), "no", rep("yes", 4), "no")
  )
rownames(mat_col) <- colnames(FCmatrix)

mat_colors <-
  list(
    time = c("pink", "chocolate4"),
    class = c("yellow1", "lightgreen"),
    TOP2i = c("darkgreen", "goldenrod")
  )
names(mat_colors$time) <- unique(mat_col$time)
names(mat_colors$class) <- unique(mat_col$class)
names(mat_colors$TOP2i) <- unique(mat_col$TOP2i)
corrFC <- cor(FCmatrix)
ComplexHeatmap::pheatmap(
  corrFC,
  display_numbers = TRUE,
  number_format = "%.2f",
  main = ("Correlation of all expressed FC values, n=14084"),
  annotation_col = mat_col,
  annotation_colors = mat_colors,
  fontsize = 10,
  fontsize_row = 8,
  angle_col = "0",
  treeheight_row = 25,
  fontsize_col = 8,
  treeheight_col = 20
)

Version Author Date
c6faf91 reneeisnowhere 2023-07-28
513ca48 reneeisnowhere 2023-07-26
4533d4a reneeisnowhere 2023-07-21
HMcorr <- ComplexHeatmap::pheatmap(
  corrFC,
  display_numbers = TRUE,
  number_format = "%.2f",
  annotation_col = mat_col,
  annotation_colors = mat_colors,
  fontsize = 10,
  fontsize_row = 8,
  angle_col = "0",
  treeheight_row = 25,
  fontsize_col = 8,
  treeheight_col = 20
)

Additional code and information can be found here

B. Venn Diagram of 3 hour DEGs

total3 <- list(sigVDA3$ENTREZID,sigVDX3$ENTREZID, sigVEP3$ENTREZID,sigVMT3$ENTREZID)
totalin_common3 <- c(sigVDA3$SYMBOL,sigVDX3$SYMBOL, sigVEP3$SYMBOL,sigVMT3$SYMBOL)


fig3hrvenn <- ggVennDiagram::ggVennDiagram(total3,
              category.names = c("DNR    \nn = 532\n",
                                 "DOX\n  n = 19\n",
                                 "EPI\n   n = 210\n",
                                 " MTX\n   n = 75\n"),
              show_intersect = FALSE,
              set_color = "black",
              category_size = c(5,5,5,5),
              label = "count",
              label_percent_digit = 1,
              label_size = 4,
              label_alpha = 0,
              caption_size = 4,
              label_color = "black",
              edge_lty = "solid", set_size = 4.5)+
  scale_x_continuous(expand = expansion(mult = .3))+
  scale_y_continuous(expand = expansion(mult = .2))+
  scale_color_paletteer_d(palette = "fishualize::Bodianus_pulchellus")+
  scale_fill_distiller(palette="Spectral", direction = -1, limits=c(0,4500))+
  labs(title = "3 hour",
       caption = paste("n =", length(unique(totalin_common3)),"genes\n "))+
  theme(plot.title = element_text(size = rel(1.5), hjust = 0.5, vjust =1),
        plot.caption=element_text(size=12))
fig3hrvenn 

Version Author Date
c6faf91 reneeisnowhere 2023-07-28
513ca48 reneeisnowhere 2023-07-26
4533d4a reneeisnowhere 2023-07-21

C. Venn Diagram of 24 hour DEGs

total24 <-
  list(sigVDA24$ENTREZID,
       sigVDX24$ENTREZID,
       sigVEP24$ENTREZID,
       sigVMT24$ENTREZID)
in_common24 <-
  c(sigVDA24$ENTREZID,
    sigVDX24$ENTREZID,
    sigVEP24$ENTREZID,
    sigVMT24$ENTREZID)


fig24hrvenn <- ggVennDiagram::ggVennDiagram(
  total24,
  category.names = c(
    "DNR \nn = 7017  \n ",
    "DOX\n n = 6645\n",
    "EPI\n n = 6328\n",
    " MTX\n   n = 1115\n "
  ),
  show_intersect = FALSE,
  set_color = "black",
  category_size = c(5, 5, 5, 5),
  label = "count",
  label_percent_digit = 1,
  label_size = 4,
  label_alpha = 0,
  label_color = "black",
  edge_lty = "solid",
  set_size = 4
) +
  scale_x_continuous(expand = expansion(mult = .3)) +
  scale_y_continuous(expand = expansion(mult = .2)) +
  scale_color_paletteer_d(palette = "fishualize::Bodianus_pulchellus") +
  scale_fill_distiller(palette = "Spectral", direction = -1) +
  labs(title = "24 hour",
       caption = paste("n =", length(unique(in_common24)), "genes\n ")) +
  
  theme(
    plot.title = element_text(
      size = rel(1.6),
      hjust = 0.5,
      vjust = 1
    ),
    plot.caption = element_text(size = 12)
  )
fig24hrvenn

Version Author Date
c6faf91 reneeisnowhere 2023-07-28
513ca48 reneeisnowhere 2023-07-26
4533d4a reneeisnowhere 2023-07-21

More information can be found here.

D. 3 KEGG Pathway analysis

kegglistDEG3 <- readRDS("data/kegglistDEG3.RDS")
list2env(kegglistDEG3, envir = .GlobalEnv)
<environment: R_GlobalEnv>
keggDEGlong3 <- list(
  "DOX" = DXdeg3k,
  "EPI" = EPdeg3k,
  "DNR" = DAdeg3k,
  "MTX" = MTdeg3k,
  "Anthracyclines" = DDEdeg3k,
  "TOP2Bi" = DDEMdeg3k
)
col_funkegg = circlize::colorRamp2(c(0, 31), c("white", "darkred"))
keggtable3 <-
  data.table::rbindlist(keggDEGlong3,
                        idcol = "deg",
                        fill = TRUE,
                        use.names = TRUE) #%>% complete(deg = names(keglistDEG3))

kegg_sig_mat3 <- keggtable3 %>%
  dplyr::select(deg, p_value, term_name) %>%
  add_row(deg = "TOP2i",
          p_value = 1,
          term_name = "Herpes simplex virus 1 infection") %>%
  mutate(
    term_name = case_match(
      term_name,
      "Cell cycle" ~ "Cell\ncycle",
      "p53 signaling pathway" ~ "p53\nsig.\npath.",
      "Base excision repair" ~ "Base\nexcision\nrepair",
      "Herpes simplex virus 1 infection" ~ "HSV1\ninfection"    ,
      "DNA replication" ~ "DNA\nrep.",
      .default = term_name
    )
  ) %>%
  pivot_wider(
    id_cols = everything(),
    names_from = "term_name",
    values_from = "p_value",
    values_fill = list(p_value = 1)
  ) %>%
  column_to_rownames('deg') %>%
  as.matrix()#

kegg_mat3 <- keggtable3 %>%
  dplyr::select(deg, log_val, term_name) %>%
  add_row(deg = "TOP2i",
          log_val = NA,
          term_name = "Herpes simplex virus 1 infection") %>%
  mutate(
    term_name = case_match(
      term_name,
      "p53 signaling pathway" ~ "p53\nsig.\npath.",
      "Base excision repair" ~ "Base\nexcision\nrepair",
      "Herpes simplex virus 1 infection" ~ "HSV1\ninfection"    ,
      "DNA replication" ~ "DNA\nrep.",
      .default = term_name
    )
  ) %>%
  pivot_wider(id_cols = everything(),
              names_from = "term_name",
              values_from = "log_val") %>%
  column_to_rownames('deg') %>%
  as.matrix()#

draw(
  Heatmap(
    kegg_mat3,
    column_title = "KEGG Pathway -log 10(p value)",
    name = "-log10 (p value)",
    cluster_rows = FALSE,
    cluster_columns = FALSE,
    column_names_rot = 0,
    column_names_centered = TRUE,
    row_names_max_width = max_text_width(rownames(kegg_mat3),
                                         gp = gpar(fontsize = 10)),
    col = col_funkegg,
    na_col = "lightyellow",
    column_labels = gt_render(c("HSV-1 infx.",
                                "p53\nsig.\npath.")),
    cell_fun = function(j, i, x, y, width, height, fill) {
      if (kegg_sig_mat3[i, j] < 0.05)
        grid.text("*", x, y, gp = gpar(fontsize = 20))
    }
  )
)

Version Author Date
c6faf91 reneeisnowhere 2023-07-28
513ca48 reneeisnowhere 2023-07-26
4533d4a reneeisnowhere 2023-07-21

More information can be found here.

E. 24 KEGG Pathway analysis

library(grid)
kegglistDEG24 <- readRDS("data/kegglistDEG24.RDS")
list2env(kegglistDEG24, envir = .GlobalEnv)
<environment: R_GlobalEnv>
keggDEGlong <- list(
  "DOX" = DXdegk,
  "EPI" = EPdegk,
  "DNR" = DAdegk,
  "MTX" = MTdegk,
  "Anthracyclines" = DDEdegk,
  "TOP2i" = DDEMdegk
)
col_funkegg = circlize::colorRamp2(c(0, 31), c("white", "darkred"))
keggtable <- data.table::rbindlist(keggDEGlong, idcol = "deg")

kegg_sig_mat <- keggtable %>%
  dplyr::select(deg, p_value, term_name) %>%
  mutate(
    term_name = case_match(
      term_name,
      "Cell cycle" ~ "Cell\ncycle",
      "p53 signaling pathway" ~ "p53\nsig.\npath.",
      "Base excision repair" ~ "Base\nexcision\nrepair",
      "DNA replication" ~ "DNA\nrep.",
      .default = term_name
    )
  ) %>%
  pivot_wider(
    id_cols = everything(),
    names_from = "term_name",
    values_from = "p_value",
    values_fill = list(p_value = 1)
  ) %>%
  column_to_rownames('deg') %>%
  as.matrix()#

kegg_mat <- keggtable %>%
  dplyr::select(deg, log_val, term_name) %>%
  mutate(
    term_name = case_match(
      term_name,
      "Cell cycle" ~ "Cell\ncycle",
      "p53 signaling pathway" ~ "p53\nsig.\npath.",
      "Base excision repair" ~ "Base\nexcision\nrepair",
      "DNA replication" ~ "DNA\nrep.",
      .default = term_name
    )
  ) %>%
  pivot_wider(id_cols = everything(),
              names_from = "term_name",
              values_from = "log_val") %>%
  column_to_rownames('deg') %>%
  as.matrix()#

Heatmap(
  kegg_mat,
  column_title = "KEGG Pathway -log p values",
  name = "-log10 (p value)",
  cluster_rows = FALSE,
  cluster_columns = FALSE,
  column_names_rot = 0,
  column_names_centered = TRUE,
  row_names_max_width = max_text_width(rownames(kegg_mat),
                                       gp = gpar(fontsize = 10)),
  col = col_funkegg,
  na_col = "lightyellow",
  column_labels = gt_render(c(
    "p53\nsig.\npath.",
    "B.E.R.",
    "Cell\ncycle",
    "DNA\nrep."
  )),
  cell_fun = function(j, i, x, y, width, height, fill) {
    if (kegg_sig_mat[i, j] < 0.05)
      grid.text("*", x, y, gp = gpar(fontsize = 20))
  }
)

Version Author Date
c6faf91 reneeisnowhere 2023-07-28
4533d4a reneeisnowhere 2023-07-21

Further KEGG analysis information and code may be found here


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] paletteer_1.5.0       gridtext_0.1.5        ComplexHeatmap_2.16.0
 [4] ggVennDiagram_1.2.3   corrplot_0.92         limma_3.56.2         
 [7] broom_1.0.5           RColorBrewer_1.1-3    ggsignif_0.6.4       
[10] cowplot_1.1.1         data.table_1.14.8     BiocGenerics_0.46.0  
[13] lubridate_1.9.2       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_3.4.3        
[22] tidyverse_2.0.0       car_3.1-2             carData_3.0-5        
[25] workflowr_1.7.1      

loaded via a namespace (and not attached):
 [1] DBI_1.1.3           rematch2_2.1.2      rlang_1.1.1        
 [4] magrittr_2.0.3      clue_0.3-64         GetoptLong_1.0.5   
 [7] git2r_0.32.0        matrixStats_1.0.0   e1071_1.7-13       
[10] compiler_4.3.1      getPass_0.2-2       png_0.1-8          
[13] callr_3.7.3         vctrs_0.6.3         pkgconfig_2.0.3    
[16] shape_1.4.6         crayon_1.5.2        fastmap_1.1.1      
[19] backports_1.4.1     magick_2.7.5        labeling_0.4.3     
[22] utf8_1.2.3          promises_1.2.1      rmarkdown_2.24     
[25] markdown_1.8        tzdb_0.4.0          ps_1.7.5           
[28] xfun_0.40           cachem_1.0.8        jsonlite_1.8.7     
[31] RVenn_1.1.0         later_1.3.1         parallel_4.3.1     
[34] cluster_2.1.4       R6_2.5.1            bslib_0.5.1        
[37] stringi_1.7.12      jquerylib_0.1.4     Rcpp_1.0.11        
[40] iterators_1.0.14    knitr_1.44          IRanges_2.34.1     
[43] httpuv_1.6.11       timechange_0.2.0    tidyselect_1.2.0   
[46] rstudioapi_0.15.0   abind_1.4-5         yaml_2.3.7         
[49] doParallel_1.0.17   codetools_0.2-19    processx_3.8.2     
[52] withr_2.5.0         evaluate_0.21       sf_1.0-14          
[55] units_0.8-4         proxy_0.4-27        xml2_1.3.5         
[58] circlize_0.4.15     pillar_1.9.0        whisker_0.4.1      
[61] KernSmooth_2.23-22  foreach_1.5.2       stats4_4.3.1       
[64] generics_0.1.3      rprojroot_2.0.3     S4Vectors_0.38.1   
[67] hms_1.1.3           commonmark_1.9.0    munsell_0.5.0      
[70] scales_1.2.1        class_7.3-22        glue_1.6.2         
[73] tools_4.3.1         fs_1.6.3            colorspace_2.1-0   
[76] cli_3.6.1           fansi_1.0.4         gtable_0.3.4       
[79] sass_0.4.7          digest_0.6.33       prismatic_1.1.1    
[82] classInt_0.4-10     rjson_0.2.21        farver_2.1.1       
[85] htmltools_0.5.6     lifecycle_1.0.3     httr_1.4.7         
[88] GlobalOptions_0.1.2