Peak Cut Off

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Last updated: 2025-08-12

Checks: 7 0

Knit directory: DXR_continue/

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File	Version	Author	Date	Message
html	7216f03	infurnoheat	2025-08-01	Build site.
Rmd	bb1f3a1	infurnoheat	2025-08-01	wflow_publish("analysis/peak_cutoff.Rmd")
html	cd6a358	infurnoheat	2025-08-01	Build site.
html	1281eed	infurnoheat	2025-07-25	Build site.
Rmd	fcda182	infurnoheat	2025-07-25	wflow_publish("analysis/peak_cutoff.Rmd")
html	3d6bcff	infurnoheat	2025-07-22	Build site.
Rmd	95b9db5	infurnoheat	2025-07-22	wflow_publish("analysis/peak_cutoff.Rmd")

---

Peak Cutoff

Loading Packages

library(tidyverse)
library(readr)
library(edgeR)
library(ComplexHeatmap)
library(data.table)
library(dplyr)
library(stringr)
library(ggplot2)
library(viridis)
library(DT)
library(kableExtra)
library(genomation)
library(GenomicRanges)
library(chromVAR) ## For FRiP analysis and differential analysis
library(DESeq2) ## For differential analysis section
library(ggpubr) ## For customizing figures
library(corrplot) ## For correlation plot
library(ggpmisc)
library(gcplyr)
library(Rsubread)

Data Initialization

sampleinfo <- read_delim("data/sample_info.tsv", delim = "\t")

Functions

drug_pal <- c("#8B006D","#DF707E","#F1B72B", "#3386DD","#707031","#41B333")
pca_plot <-
  function(df,
           col_var = NULL,
           shape_var = NULL,
           title = "") {
    ggplot(df) + geom_point(aes_string(
      x = "PC1",
      y = "PC2",
      color = col_var,
      shape = shape_var
    ),
    size = 5) +
      labs(title = title, x = "PC 1", y = "PC 2") +
      scale_color_manual(values = c(
        "#8B006D",
        "#DF707E",
        "#F1B72B",
        "#3386DD",
        "#707031",
        "#41B333"
      ))
  }
pca_var_plot <- function(pca) {
  # x: class == prcomp
  pca.var <- pca$sdev ^ 2
  pca.prop <- pca.var / sum(pca.var)
  var.plot <-
    qplot(PC, prop, data = data.frame(PC = 1:length(pca.prop),
                                      prop = pca.prop)) +
    labs(title = 'Variance contributed by each PC',
         x = 'PC', y = 'Proportion of variance')
  plot(var.plot)
}

calc_pca <- function(x) {
  # Performs principal components analysis with prcomp
  # x: a sample-by-gene numeric matrix
  prcomp(x, scale. = TRUE, retx = TRUE)
}

get_regr_pval <- function(mod) {
  # Returns the p-value for the Fstatistic of a linear model
  # mod: class lm
  stopifnot(class(mod) == "lm")
  fstat <- summary(mod)$fstatistic
  pval <- 1 - pf(fstat[1], fstat[2], fstat[3])
  return(pval)
}

plot_versus_pc <- function(df, pc_num, fac) {
  # df: data.frame
  # pc_num: numeric, specific PC for plotting
  # fac: column name of df for plotting against PC
  pc_char <- paste0("PC", pc_num)
  # Calculate F-statistic p-value for linear model
  pval <- get_regr_pval(lm(df[, pc_char] ~ df[, fac]))
  if (is.numeric(df[, f])) {
    ggplot(df, aes_string(x = f, y = pc_char)) + geom_point() +
      geom_smooth(method = "lm") + labs(title = sprintf("p-val: %.2f", pval))
  } else {
    ggplot(df, aes_string(x = f, y = pc_char)) + geom_boxplot() +
      labs(title = sprintf("p-val: %.2f", pval))
  }
}
x_axis_labels = function(labels, every_nth = 1, ...) {
  axis(side = 1,
       at = seq_along(labels),
       labels = F)
  text(
    x = (seq_along(labels))[seq_len(every_nth) == 1],
    y = par("usr")[3] - 0.075 * (par("usr")[4] - par("usr")[3]),
    labels = labels[seq_len(every_nth) == 1],
    xpd = TRUE,
    ...
  )
}

Peak Cut Off Analysis via Elbow Method

Cut Off Analysis for H3K27ac

H3K27ac <- sampleinfo %>%
  dplyr::filter(Histone_Mark=="H3K27ac")
cutoff <- data.frame(matrix(nrow = 0, ncol = 6))
colnames(cutoff) = c("Sample", "pscore", "qscore", "npeaks", "lpeaks", "avelpeak")
for (sample in H3K27ac$`Library ID`) {
  filename <- paste("data/peaks/H3K27ac/", sample, "_macs3_noModel_cutoff_analysis.txt", sep = "")
  temp <- read_delim(filename, delim = "\t")
  temp$Sample <- sample
  cutoff <- rbind(cutoff, temp)
}
H3K27ac <- left_join(H3K27ac, cutoff, by =c("Library ID"="Sample"))
H3K27ac %>%  
  ggplot(., aes(x=H3K27ac$qscore, y=H3K27ac$npeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K27ac$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Peak Counts",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K27ac 1-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

H3K27ac %>%  
  ggplot(., aes(x=H3K27ac$qscore, y=H3K27ac$lpeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K27ac$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K27ac 2-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

H3K27ac %>%  
  ggplot(., aes(x=H3K27ac$qscore, y=H3K27ac$avelpeak, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K27ac$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Average Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K27ac 3-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

Cut Off Analysis for H3K27me3

H3K27me3 <- sampleinfo %>%
  dplyr::filter(Histone_Mark=="H3K27me3")
cutoff <- data.frame(matrix(nrow = 0, ncol = 6))
colnames(cutoff) = c("Sample", "pscore", "qscore", "npeaks", "lpeaks", "avelpeak")
for (sample in H3K27me3$`Library ID`) {
  filename <- paste("data/peaks/H3K27me3/", sample, "_macs3_cutoff_analysis.txt", sep = "")
  temp <- read_delim(filename, delim = "\t")
  temp$Sample <- sample
  cutoff <- rbind(cutoff, temp)
}
H3K27me3 <- left_join(H3K27me3, cutoff, by =c("Library ID"="Sample"))

H3K27me3 <- H3K27me3[(H3K27me3$pscore >= 0.6),]

H3K27me3 %>%  
  ggplot(., aes(x=H3K27me3$qscore, y=H3K27me3$npeaks, color = 'Library ID'))+
  geom_line(size=1)+
  # geom_point(size=2,alpha =0.7)+
  scale_x_continuous(breaks = seq(0, max(H3K27me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Peak Counts",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K27me3 1-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

H3K27me3 %>%  
  ggplot(., aes(x=H3K27me3$qscore, y=H3K27me3$lpeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K27me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K27me3 2-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

H3K27me3 %>%  
  ggplot(., aes(x=H3K27me3$qscore, y=H3K27me3$avelpeak, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K27me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Average Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K27me3 3-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

Cut Off Analysis for H3K36me3

H3K36me3 <- sampleinfo %>%
  dplyr::filter(Histone_Mark=="H3K36me3")
cutoff <- data.frame(matrix(nrow = 0, ncol = 6))
colnames(cutoff) = c("Sample", "pscore", "qscore", "npeaks", "lpeaks", "avelpeak")
for (sample in H3K36me3$`Library ID`) {
  filename = paste("data/peaks/H3K36me3/", sample, "_macs3_cutoff_analysis.txt", sep = "")
  temp <- read_delim(filename, delim = "\t")
  temp$Sample <- sample
  cutoff <- rbind(cutoff, temp)
}
H3K36me3 <- left_join(H3K36me3, cutoff, by =c("Library ID"="Sample"))

H3K36me3 <- H3K36me3[(H3K36me3$pscore >= 0.6),]

H3K36me3 %>%  
  ggplot(., aes(x=H3K36me3$qscore, y=H3K36me3$npeaks, color = 'Library ID'))+
  geom_line(size=1)+
  # geom_point(size=2,alpha =0.7)+
  scale_x_continuous(breaks = seq(0, max(H3K36me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Peak Counts",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K36me3 1-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

H3K36me3 %>%  
  ggplot(., aes(x=H3K36me3$qscore, y=H3K36me3$lpeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K36me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K36me3 2-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

H3K36me3 %>%  
  ggplot(., aes(x=H3K36me3$qscore, y=H3K36me3$avelpeak, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K36me3$qscore), by =1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Average Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K36me3 3-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

Cut Off Analysis for H3K9me3

H3K9me3 <- sampleinfo %>%
  dplyr::filter(Histone_Mark=="H3K9me3")
cutoff <- data.frame(matrix(nrow = 0, ncol = 6))
colnames(cutoff) = c("Sample", "pscore", "qscore", "npeaks", "lpeaks", "avelpeak")
for (sample in H3K9me3$`Library ID`) {
  filename = paste("data/peaks/H3K9me3/", sample, "_macs3_noModel_cutoff_analysis.txt", sep = "")
  temp <- read_delim(filename, delim = "\t")
  temp$Sample <- sample
  cutoff <- rbind(cutoff, temp)
}
H3K9me3 <- left_join(H3K9me3, cutoff, by =c("Library ID"="Sample"))

H3K9me3 %>%  
  ggplot(., aes(x=H3K9me3$qscore, y=H3K9me3$npeaks, color = 'Library ID'))+
  geom_line(size=1)+
  # geom_point(size=2,alpha =0.7)+
  scale_x_continuous(breaks = seq(0, max(H3K9me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Peak Counts",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K9me3 1-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

H3K9me3 %>%  
  ggplot(., aes(x=H3K9me3$qscore, y=H3K9me3$lpeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K9me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K9me3 2-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

H3K9me3 %>%  
  ggplot(., aes(x=H3K9me3$qscore, y=H3K9me3$avelpeak, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K9me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Average Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "peak cutoff H3K9me3 3-1.png"

Version	Author	Date
3d6bcff	infurnoheat	2025-07-22

Cut Off For Broad Peaks as Narrow

H3K27me3 <- sampleinfo %>%
  dplyr::filter(Histone_Mark=="H3K27me3") %>%
  dplyr::filter(!Treatment=="5FU")
cutoff <- data.frame(matrix(nrow = 0, ncol = 6))
colnames(cutoff) = c("Sample", "pscore", "qscore", "npeaks", "lpeaks", "avelpeak")
for (sample in H3K27me3$`Library ID`) {
  filename <- paste("data/peaks/H3K27me3/", sample, "_narrow_cutoff_analysis.txt", sep = "")
  temp <- read_delim(filename, delim = "\t")
  temp$Sample <- sample
  cutoff <- rbind(cutoff, temp)
}
H3K27me3 <- left_join(H3K27me3, cutoff, by =c("Library ID"="Sample"))

H3K27me3 <- H3K27me3 %>%
  dplyr::filter(qscore > 0.6)

H3K27me3 %>%  
  ggplot(., aes(x=H3K27me3$qscore, y=H3K27me3$npeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K27me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "H3K27me3 narrow 1-1.png"

Version	Author	Date
1281eed	infurnoheat	2025-07-25

H3K27me3 %>%  
  ggplot(., aes(x=H3K27me3$qscore, y=H3K27me3$lpeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K27me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "H3K27me3 narrow 2-1.png"

Version	Author	Date
1281eed	infurnoheat	2025-07-25

H3K27me3 %>%  
  ggplot(., aes(x=H3K27me3$qscore, y=H3K27me3$avelpeak, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K27me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "H3K27me3 narrow 3-1.png"

Version	Author	Date
1281eed	infurnoheat	2025-07-25

H3K36me3 <- sampleinfo %>%
  dplyr::filter(Histone_Mark=="H3K36me3") %>%
  dplyr::filter(!Treatment=="5FU")
cutoff <- data.frame(matrix(nrow = 0, ncol = 6))
colnames(cutoff) = c("Sample", "pscore", "qscore", "npeaks", "lpeaks", "avelpeak")
for (sample in H3K36me3$`Library ID`) {
  filename <- paste("data/peaks/H3K36me3/", sample, "_narrow_cutoff_analysis.txt", sep = "")
  temp <- read_delim(filename, delim = "\t")
  temp$Sample <- sample
  cutoff <- rbind(cutoff, temp)
}
H3K36me3 <- left_join(H3K36me3, cutoff, by =c("Library ID"="Sample"))

H3K36me3 <- H3K36me3 %>%
  dplyr::filter(qscore > 0.6)

H3K36me3 %>%  
  ggplot(., aes(x=H3K36me3$qscore, y=H3K36me3$npeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K36me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "H3K36me3 narrow 1-1.png"

Version	Author	Date
1281eed	infurnoheat	2025-07-25

H3K36me3 %>%  
  ggplot(., aes(x=H3K36me3$qscore, y=H3K36me3$lpeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K36me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "H3K36me3 narrow 2-1.png"

Version	Author	Date
1281eed	infurnoheat	2025-07-25

H3K36me3 %>%  
  ggplot(., aes(x=H3K36me3$qscore, y=H3K36me3$avelpeak, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K36me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "H3K36me3 narow 3-1.png"

Version	Author	Date
1281eed	infurnoheat	2025-07-25

H3K9me3 <- sampleinfo %>%
  dplyr::filter(Histone_Mark=="H3K9me3") %>%
  dplyr::filter(!Treatment=="5FU")
cutoff <- data.frame(matrix(nrow = 0, ncol = 6))
colnames(cutoff) = c("Sample", "pscore", "qscore", "npeaks", "lpeaks", "avelpeak")
for (sample in H3K9me3$`Library ID`) {
  filename <- paste("data/peaks/H3K9me3/", sample, "_narrow_cutoff_analysis.txt", sep = "")
  temp <- read_delim(filename, delim = "\t")
  temp$Sample <- sample
  cutoff <- rbind(cutoff, temp)
}
H3K9me3 <- left_join(H3K9me3, cutoff, by =c("Library ID"="Sample"))

H3K9me3 <- H3K9me3 %>%
  dplyr::filter(qscore > 0.6)

H3K9me3 %>%  
  ggplot(., aes(x=H3K9me3$qscore, y=H3K9me3$lpeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K9me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "H3K9me3 narrow 1-1.png"

Version	Author	Date
1281eed	infurnoheat	2025-07-25

H3K9me3 %>%  
  ggplot(., aes(x=H3K9me3$qscore, y=H3K9me3$lpeaks, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K9me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "H3K9me3 narrow 2-1.png"

Version	Author	Date
1281eed	infurnoheat	2025-07-25

H3K9me3 %>%  
  ggplot(., aes(x=H3K9me3$qscore, y=H3K9me3$avelpeak, color = 'Library ID'))+
  geom_line(size=1)+
  scale_x_continuous(breaks = seq(0, max(H3K9me3$qscore), by = 1))+
  facet_wrap(~`Library ID`, scales = "free", ncol = 5, switch = "y")+
  labs(title = "",
       x = "Q Score",
       y = "Total Peak Lengths",
       color= "Sample")+
  theme_minimal()

Past versions of "H3K9me3 narow 3-1.png"

Version	Author	Date
1281eed	infurnoheat	2025-07-25

Session information

sessionInfo()

R version 4.4.2 (2024-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)

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] stats4    grid      stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] Rsubread_2.20.0             gcplyr_1.12.0              
 [3] ggpmisc_0.6.2               ggpp_0.5.9                 
 [5] corrplot_0.95               ggpubr_0.6.1               
 [7] DESeq2_1.46.0               SummarizedExperiment_1.36.0
 [9] Biobase_2.66.0              MatrixGenerics_1.18.1      
[11] matrixStats_1.5.0           chromVAR_1.28.0            
[13] GenomicRanges_1.58.0        GenomeInfoDb_1.42.3        
[15] IRanges_2.40.1              S4Vectors_0.44.0           
[17] BiocGenerics_0.52.0         genomation_1.38.0          
[19] kableExtra_1.4.0            DT_0.33                    
[21] viridis_0.6.5               viridisLite_0.4.2          
[23] data.table_1.17.8           ComplexHeatmap_2.22.0      
[25] edgeR_4.4.2                 limma_3.62.2               
[27] lubridate_1.9.4             forcats_1.0.0              
[29] stringr_1.5.1               dplyr_1.1.4                
[31] purrr_1.1.0                 readr_2.1.5                
[33] tidyr_1.3.1                 tibble_3.3.0               
[35] ggplot2_3.5.2               tidyverse_2.0.0            
[37] workflowr_1.7.1            

loaded via a namespace (and not attached):
  [1] splines_4.4.2               later_1.4.2                
  [3] BiocIO_1.16.0               bitops_1.0-9               
  [5] R.oo_1.27.1                 XML_3.99-0.18              
  [7] DirichletMultinomial_1.48.0 lifecycle_1.0.4            
  [9] rstatix_0.7.2               pwalign_1.2.0              
 [11] doParallel_1.0.17           rprojroot_2.1.0            
 [13] vroom_1.6.5                 MASS_7.3-65                
 [15] processx_3.8.6              lattice_0.22-7             
 [17] backports_1.5.0             magrittr_2.0.3             
 [19] plotly_4.11.0               sass_0.4.10                
 [21] rmarkdown_2.29              jquerylib_0.1.4            
 [23] yaml_2.3.10                 plotrix_3.8-4              
 [25] httpuv_1.6.16               DBI_1.2.3                  
 [27] CNEr_1.42.0                 RColorBrewer_1.1-3         
 [29] abind_1.4-8                 zlibbioc_1.52.0            
 [31] R.utils_2.13.0              RCurl_1.98-1.17            
 [33] git2r_0.36.2                circlize_0.4.16            
 [35] GenomeInfoDbData_1.2.13     seqLogo_1.72.0             
 [37] MatrixModels_0.5-4          annotate_1.84.0            
 [39] svglite_2.2.1               codetools_0.2-20           
 [41] DelayedArray_0.32.0         xml2_1.3.8                 
 [43] tidyselect_1.2.1            shape_1.4.6.1              
 [45] UCSC.utils_1.2.0            farver_2.1.2               
 [47] GenomicAlignments_1.42.0    jsonlite_2.0.0             
 [49] GetoptLong_1.0.5            Formula_1.2-5              
 [51] survival_3.8-3              iterators_1.0.14           
 [53] systemfonts_1.2.3           foreach_1.5.2              
 [55] tools_4.4.2                 TFMPvalue_0.0.9            
 [57] Rcpp_1.1.0                  glue_1.8.0                 
 [59] gridExtra_2.3               SparseArray_1.6.2          
 [61] xfun_0.52                   withr_3.0.2                
 [63] fastmap_1.2.0               SparseM_1.84-2             
 [65] callr_3.7.6                 caTools_1.18.3             
 [67] digest_0.6.37               timechange_0.3.0           
 [69] R6_2.6.1                    mime_0.13                  
 [71] seqPattern_1.38.0           textshaping_1.0.1          
 [73] colorspace_2.1-1            GO.db_3.20.0               
 [75] gtools_3.9.5                poweRlaw_1.0.0             
 [77] dichromat_2.0-0.1           RSQLite_2.4.2              
 [79] R.methodsS3_1.8.2           generics_0.1.4             
 [81] rtracklayer_1.66.0          httr_1.4.7                 
 [83] htmlwidgets_1.6.4           S4Arrays_1.6.0             
 [85] TFBSTools_1.44.0            whisker_0.4.1              
 [87] pkgconfig_2.0.3             gtable_0.3.6               
 [89] blob_1.2.4                  impute_1.80.0              
 [91] XVector_0.46.0              htmltools_0.5.8.1          
 [93] carData_3.0-5               clue_0.3-66                
 [95] scales_1.4.0                png_0.1-8                  
 [97] knitr_1.50                  rstudioapi_0.17.1          
 [99] tzdb_0.5.0                  reshape2_1.4.4             
[101] rjson_0.2.23                curl_6.4.0                 
[103] cachem_1.1.0                GlobalOptions_0.1.2        
[105] KernSmooth_2.23-26          parallel_4.4.2             
[107] miniUI_0.1.2                AnnotationDbi_1.68.0       
[109] restfulr_0.0.16             pillar_1.11.0              
[111] vctrs_0.6.5                 promises_1.3.3             
[113] car_3.1-3                   xtable_1.8-4               
[115] cluster_2.1.8.1             evaluate_1.0.4             
[117] cli_3.6.5                   locfit_1.5-9.12            
[119] compiler_4.4.2              Rsamtools_2.22.0           
[121] rlang_1.1.6                 crayon_1.5.3               
[123] ggsignif_0.6.4              labeling_0.4.3             
[125] ps_1.9.1                    getPass_0.2-4              
[127] plyr_1.8.9                  fs_1.6.6                   
[129] stringi_1.8.7               gridBase_0.4-7             
[131] BiocParallel_1.40.2         Biostrings_2.74.1          
[133] lazyeval_0.2.2              quantreg_6.1               
[135] Matrix_1.7-3                BSgenome_1.74.0            
[137] hms_1.1.3                   bit64_4.6.0-1              
[139] KEGGREST_1.46.0             statmod_1.5.0              
[141] shiny_1.11.1                broom_1.0.9                
[143] memoise_2.0.1               bslib_0.9.0                
[145] bit_4.6.0                   polynom_1.4-1