Enrich Go Diff Expression

---
title: "TCGA Go Enrich All Studies"
author: "MacKenzie Wells"
date: "2024-09-19"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.

When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

```{r for TCGA ACC}
# Read the XIST file 
xist_csv <- read.csv("C:/Users/Owner/Downloads/XISTloss_dge_ALLtissues.csv")

# View the first few rows of the data
head(xist_csv)

# Read the DDX3Y file
DDX3Y_csv <- read.csv("C:/Users/Owner/Downloads/DDX3Yloss_dge_ALLtissues.csv")

#View head of DDX3Y
head(DDX3Y_csv)

###########################################
##Load cluster profiler, obtain Diff expressed genes
###########################################
#Install packages

# Install the required packages
#BiocManager::install(c("GenomeInfoDbData", "clusterProfiler", "org.Hs.eg.db"))
#BiocManager::install("GO.db")
#BiocManager::install("HDO.db")
#BiocManager::install("clusterProfiler", force = TRUE)


#install.packages("dplyr")
library(dplyr)


library(clusterProfiler)
library(org.Hs.eg.db)
library(ggplot2)

############################################################
#pull pvalues for acc 

# View column names 
colnames(xist_csv)

#study
study <- c("TCGA_ACC")

#filter pvalues < 0.05 but only to TCGA ACC
filtered_pval_acc <- subset(xist_csv, TCGA.ACC_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-ACC
gene_list_acc <- filtered_pval_acc$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_acc)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_acc)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_acc <- enrichGO(gene = mapped_genes,
                      OrgDb = org.Hs.eg.db,
                      keyType = "SYMBOL",
                      ont = "BP", 
                      pAdjustMethod = "BH",
                      qvalueCutoff = 1)

# View results
head(go_en_acc)

# make the go en into a df
go_en_acc_df <- as.data.frame(go_en_acc)

#head df
head(go_en_acc_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_acc, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-ACC (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_acc_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-ACC",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

print(plot)

###########################
#top 10 GO terms for XIST loss in TCGA-ACC
###########################

barplot10 <- barplot(go_en_acc, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-ACC")

#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r TCGA CESC}

############################################################
#pull pvalues for CESC 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_CESC")

#filter pvalues < 0.05 but only to TCGA CESC
filtered_pval_CESC <- subset(xist_csv, TCGA.CESC_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-CESC
gene_list_CESC <- filtered_pval_CESC$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_CESC)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_CESC)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_CESC <- enrichGO(gene = mapped_genes,
                      OrgDb = org.Hs.eg.db,
                      keyType = "SYMBOL",
                      ont = "BP", 
                      pAdjustMethod = "BH",
                      qvalueCutoff = 1)

# View results
head(go_en_CESC)

# make the go en into a df
go_en_CESC_df <- as.data.frame(go_en_CESC)

#head df
head(go_en_CESC_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_CESC, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-CESC (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_CESC_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-CESC",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-CESC
###########################

barplot10 <- barplot(go_en_CESC, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-CESC")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)


```

``` {r BLCA}

#####
#BLCA
#####

study <- c("TCGA_BLCA")

#filter all pvalues < 0.05 FOR BLCA
filtered_pval_BLCA <- subset(xist_csv, TCGA.BLCA_P.Value < 0.05)
head(filtered_pval_BLCA)
# Extract gene list from the filtered data for TCGA-ACC
gene_list_BLCA <- filtered_pval_BLCA$genes
head(gene_list_BLCA)

#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list_BLCA <- sub("\\..*", "", gene_list)

# View the cleaned list
head(cleaned_gene_list_BLCA)

# some genes will not be mapped (7.9%) because ???
unmapped_genes_BLCA <- cleaned_gene_list_BLCA[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes_BLCA

# Convert cleaned ENS to Gene Symbols
gene_conversion_BLCA <- bitr(cleaned_gene_list_BLCA, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion_BLCA)


# Proceed with the mapped genes
mapped_genes_BLCA <- gene_conversion_BLCA$SYMBOL

# Perform GO enrichment
go_en_BLCA <- enrichGO(gene = mapped_genes,
                      OrgDb = org.Hs.eg.db,
                      keyType = "SYMBOL",
                      ont = "BP", 
                      pAdjustMethod = "BH",
                      qvalueCutoff = 1)

# View results
head(go_en_BLCA)

# make the go en into a df
go_en_BLCA_df <- as.data.frame(go_en_BLCA)

#head df
head(go_en_BLCA_df)


#######################
# bar plot creation!
#######################




#make data readable to plots
go_plot_data_BLCA <- go_en_BLCA_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes

# Create bar plot
plot <- ggplot(go_plot_data_BLCA, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-BLCA",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()



# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot10 <- barplot(go_en_BLCA, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-BLCA")

print(barplot10)
#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)




```
```{r BRCA}
#BRCA


study <- c("TCGA_BRCA")

#filter all pvalues < 0.05 FOR BRCA
filtered_pval_BRCA <- subset(xist_csv, TCGA.BRCA_P.Value < 0.05)
head(filtered_pval_BRCA)
# Extract gene list from the filtered data for TCGA-BRCA
gene_list_BRCA <- filtered_pval_BRCA$genes
head(gene_list_BRCA)

#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list_BRCA <- sub("\\..*", "", gene_list)

# View the cleaned list
head(cleaned_gene_list_BRCA)

# some genes will not be mapped (7.9%) because ???
unmapped_genes_BRCA <- cleaned_gene_list[!cleaned_gene_list_BRCA %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes_BRCA

# Convert cleaned ENS to Gene Symbols
gene_conversion_BRCA <- bitr(cleaned_gene_list_BRCA, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion_BRCA)


# Proceed with the mapped genes
mapped_genes_BRCA <- gene_conversion_BRCA$SYMBOL

# Perform GO enrichment
go_en_BRCA <- enrichGO(gene = mapped_genes,
                      OrgDb = org.Hs.eg.db,
                      keyType = "SYMBOL",
                      ont = "BP", 
                      pAdjustMethod = "BH",
                      qvalueCutoff = 1)

# View results
head(go_en_BRCA)

# make the go en into a df
go_en_BRCA_df <- as.data.frame(go_en_BRCA)

#head df
head(go_en_BRCA_df)


#######################
# bar plot creation!
#######################


#make data readable to plots
go_plot_data_BRCA <- go_en_BRCA_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes

# Create bar plot
plot <- ggplot(go_plot_data_BRCA, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-BRCA",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()



###########################
#top 10 GO terms for XIST loss in TCGA-BRCA
###########################

barplot10 <- barplot(go_en_BRCA, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-BRCA")


#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{R COHL}


############################################################
#pull pvalues for CHOL 

# View column names 
colnames(xist_csv)

#study
study <- c("TCGA_CHOL")

#filter pvalues < 0.05 but only to TCGA CHOL
filtered_pval_CHOL <- subset(xist_csv, TCGA.CHOL_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-CHOL
gene_list_CHOL <- filtered_pval_CHOL$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_CHOL)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_CHOL)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_CHOL <- enrichGO(gene = mapped_genes,
                      OrgDb = org.Hs.eg.db,
                      keyType = "SYMBOL",
                      ont = "BP", 
                      pAdjustMethod = "BH",
                      qvalueCutoff = 1)

# View results
head(go_en_CHOL)

# make the go en into a df
go_en_CHOL_df <- as.data.frame(go_en_CHOL)

#head df
head(go_en_CHOL_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_CHOL, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-CHOL (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_CHOL_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-CHOL",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

print(plot)

###########################
#top 10 GO terms for XIST loss in TCGA-CHOL
###########################

barplot10 <- barplot(go_en_CHOL, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-CHOL")

#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

``` {r COAD}

############################################################
#pull pvalues for COAD 

# View column names 
colnames(xist_csv)

#study
study <- c("TCGA_COAD")

#filter pvalues < 0.05 but only to TCGA COAD
filtered_pval_COAD <- subset(xist_csv, TCGA.COAD_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-COAD
gene_list_COAD <- filtered_pval_COAD$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_COAD)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_COAD)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_COAD <- enrichGO(gene = mapped_genes,
                      OrgDb = org.Hs.eg.db,
                      keyType = "SYMBOL",
                      ont = "BP", 
                      pAdjustMethod = "BH",
                      qvalueCutoff = 1)

# View results
head(go_en_COAD)

# make the go en into a df
go_en_COAD_df <- as.data.frame(go_en_COAD)

#head df
head(go_en_COAD_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_COAD, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-COAD (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_COAD_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-COAD",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-COAD
###########################

barplot10 <- barplot(go_en_COAD, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-COAD")

#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r DLBC}

############################################################
#pull pvalues for DLBC 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_DLBC")

#filter pvalues < 0.05 but only to TCGA DLBC
filtered_pval_DLBC <- subset(xist_csv, TCGA.DLBC_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-DLBC
gene_list_DLBC <- filtered_pval_DLBC$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_DLBC)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_DLBC)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_DLBC <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_DLBC)

# make the go en into a df
go_en_DLBC_df <- as.data.frame(go_en_DLBC)

#head df
head(go_en_DLBC_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_DLBC, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-DLBC (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_DLBC_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-DLBC",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-DLBC
###########################

barplot10 <- barplot(go_en_DLBC, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-DLBC")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)




```

```{r GBM}


############################################################
#pull pvalues for GBM 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_GBM")

#filter pvalues < 0.05 but only to TCGA GBM
filtered_pval_GBM <- subset(xist_csv, TCGA.GBM_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-GBM
gene_list_GBM <- filtered_pval_GBM$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_GBM)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_GBM)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_GBM <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_GBM)

# make the go en into a df
go_en_GBM_df <- as.data.frame(go_en_GBM)

#head df
head(go_en_GBM_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_GBM, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-GBM (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_GBM_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-GBM",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-GBM
###########################

barplot10 <- barplot(go_en_GBM, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-GBM")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r HNSC}
############################################################
#pull pvalues for HNSC 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_HNSC")

#filter pvalues < 0.05 but only to TCGA HNSC
filtered_pval_HNSC <- subset(xist_csv, TCGA.HNSC_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-HNSC
gene_list_HNSC <- filtered_pval_HNSC$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_HNSC)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_HNSC)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_HNSC <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_HNSC)

# make the go en into a df
go_en_HNSC_df <- as.data.frame(go_en_HNSC)

#head df
head(go_en_HNSC_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_HNSC, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-HNSC (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_HNSC_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-HNSC",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-HNSC
###########################

barplot10 <- barplot(go_en_HNSC, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-HNSC")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r KICH}
############################################################
#pull pvalues for KICH 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_KICH")

#filter pvalues < 0.05 but only to TCGA KICH
filtered_pval_KICH <- subset(xist_csv, TCGA.KICH_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-KICH
gene_list_KICH <- filtered_pval_KICH$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_KICH)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_KICH)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_KICH <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_KICH)

# make the go en into a df
go_en_KICH_df <- as.data.frame(go_en_KICH)

#head df
head(go_en_KICH_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_KICH, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-KICH (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_KICH_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-KICH",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-KICH
###########################

barplot10 <- barplot(go_en_KICH, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-KICH")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r KIRC}
############################################################
#pull pvalues for KIRC 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_KIRC")

#filter pvalues < 0.05 but only to TCGA KIRC
filtered_pval_KIRC <- subset(xist_csv, TCGA.KIRC_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-KIRC
gene_list_KIRC <- filtered_pval_KIRC$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_KIRC)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_KIRC)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_KIRC <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_KIRC)

# make the go en into a df
go_en_KIRC_df <- as.data.frame(go_en_KIRC)

#head df
head(go_en_KIRC_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_KIRC, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-KIRC (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_KIRC_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-KIRC",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-KIRC
###########################

barplot10 <- barplot(go_en_KIRC, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-KIRC")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)


```

```{r KIRP}

############################################################
#pull pvalues for KIRP 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_KIRP")

#filter pvalues < 0.05 but only to TCGA KIRP
filtered_pval_KIRP <- subset(xist_csv, TCGA.KIRP_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-KIRP
gene_list_KIRP <- filtered_pval_KIRP$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_KIRP)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_KIRP)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_KIRP <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_KIRP)

# make the go en into a df
go_en_KIRP_df <- as.data.frame(go_en_KIRP)

#head df
head(go_en_KIRP_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_KIRP, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-KIRP (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_KIRP_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-KIRP",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-KIRP
###########################

barplot10 <- barplot(go_en_KIRP, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-KIRP")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r LGG}

############################################################
#pull pvalues for LGG 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_LGG")

#filter pvalues < 0.05 but only to TCGA LGG
filtered_pval_LGG <- subset(xist_csv, TCGA.LGG_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-LGG
gene_list_LGG <- filtered_pval_LGG$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_LGG)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_LGG)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_LGG <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_LGG)

# make the go en into a df
go_en_LGG_df <- as.data.frame(go_en_LGG)

#head df
head(go_en_LGG_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_LGG, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-LGG (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_LGG_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-LGG",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-LGG
###########################

barplot10 <- barplot(go_en_LGG, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-LGG")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)


```

```{r LIHC}
############################################################
#pull pvalues for LIHC 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_LIHC")

#filter pvalues < 0.05 but only to TCGA LIHC
filtered_pval_LIHC <- subset(xist_csv, TCGA.LIHC_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-LIHC
gene_list_LIHC <- filtered_pval_LIHC$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_LIHC)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_LIHC)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_LIHC <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_LIHC)

# make the go en into a df
go_en_LIHC_df <- as.data.frame(go_en_LIHC)

#head df
head(go_en_LIHC_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_LIHC, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-LIHC (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_LIHC_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-LIHC",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-LIHC
###########################

barplot10 <- barplot(go_en_LIHC, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-LIHC")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r LUAD}

############################################################
#pull pvalues for LUAD 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_LUAD")

#filter pvalues < 0.05 but only to TCGA LUAD
filtered_pval_LUAD <- subset(xist_csv, TCGA.LUAD_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-LUAD
gene_list_LUAD <- filtered_pval_LUAD$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_LUAD)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_LUAD)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_LUAD <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_LUAD)

# make the go en into a df
go_en_LUAD_df <- as.data.frame(go_en_LUAD)

#head df
head(go_en_LUAD_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_LUAD, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-LUAD (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_LUAD_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-LUAD",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-LUAD
###########################

barplot10 <- barplot(go_en_LUAD, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-LUAD")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r LUSC}

############################################################
#pull pvalues for LUSC 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_LUSC")

#filter pvalues < 0.05 but only to TCGA LUSC
filtered_pval_LUSC <- subset(xist_csv, TCGA.LUSC_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-LUSC
gene_list_LUSC <- filtered_pval_LUSC$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_LUSC)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_LUSC)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_LUSC <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_LUSC)

# make the go en into a df
go_en_LUSC_df <- as.data.frame(go_en_LUSC)

#head df
head(go_en_LUSC_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_LUSC, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-LUSC (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_LUSC_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-LUSC",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-LUSC
###########################

barplot10 <- barplot(go_en_LUSC, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-LUSC")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r MESO}
############################################################
#pull pvalues for MESO 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_MESO")

#filter pvalues < 0.05 but only to TCGA MESO
filtered_pval_MESO <- subset(xist_csv, TCGA.MESO_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-MESO
gene_list_MESO <- filtered_pval_MESO$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_MESO)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_MESO)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_MESO <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_MESO)

# make the go en into a df
go_en_MESO_df <- as.data.frame(go_en_MESO)

#head df
head(go_en_MESO_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_MESO, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-MESO (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_MESO_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-MESO",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-MESO
###########################

barplot10 <- barplot(go_en_MESO, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-MESO")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r OV}
############################################################
#pull pvalues for OV 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_OV")

#filter pvalues < 0.05 but only to TCGA OV
filtered_pval_OV <- subset(xist_csv, TCGA.OV_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-OV
gene_list_OV <- filtered_pval_OV$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_OV)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remove version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_OV)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_OV <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_OV)

# make the go en into a df
go_en_OV_df <- as.data.frame(go_en_OV)

#head df
head(go_en_OV_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_OV, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-OV (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_OV_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-OV",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-OV
###########################

barplot10 <- barplot(go_en_OV, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-OV")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r PAAD}

############################################################
#pull pvalues for paad 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_paad")

#filter pvalues < 0.05 but only to TCGA paad
filtered_pval_paad <- subset(xist_csv, TCGA.PAAD_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-paad
gene_list_paad <- filtered_pval_paad$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_paad)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Rempaade version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_paad)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_paad <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_paad)

# make the go en into a df
go_en_paad_df <- as.data.frame(go_en_paad)

#head df
head(go_en_paad_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_paad, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-paad (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_paad_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-paad",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-paad
###########################

barplot10 <- barplot(go_en_paad, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-paad")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r PCPG}

############################################################
#pull pvalues for PCPG 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_PCPG")

#filter pvalues < 0.05 but only to TCGA PCPG
filtered_pval_PCPG <- subset(xist_csv, TCGA.PCPG_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-PCPG
gene_list_PCPG <- filtered_pval_PCPG$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_PCPG)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# RemPCPGe version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_PCPG)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_PCPG <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_PCPG)

# make the go en into a df
go_en_PCPG_df <- as.data.frame(go_en_PCPG)

#head df
head(go_en_PCPG_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_PCPG, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-PCPG (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_PCPG_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-PCPG",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-PCPG
###########################

barplot10 <- barplot(go_en_PCPG, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-PCPG")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r READ}

############################################################
#pull pvalues for read 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_read")

#filter pvalues < 0.05 but only to TCGA read
filtered_pval_read <- subset(xist_csv, TCGA.READ_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-read
gene_list_read <- filtered_pval_read$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_read)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# Remreade version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_read)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_read <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_read)

# make the go en into a df
go_en_read_df <- as.data.frame(go_en_read)

#head df
head(go_en_read_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_read, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-read (Unadjusted p-values)")


#make data readable to plots
go_plot_data <- go_en_read_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-read",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-read
###########################

barplot10 <- barplot(go_en_read, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-read")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r SARC}

############################################################
#pull pvalues for SARC 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_SARC")

#filter pvalues < 0.05 but only to TCGA SARC
filtered_pval_SARC <- subset(xist_csv, TCGA.SARC_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-SARC
gene_list_SARC <- filtered_pval_SARC$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_SARC)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# RemSARCe version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_SARC)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_SARC <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_SARC)

# make the go en into a df
go_en_SARC_df <- as.data.frame(go_en_SARC)

#head df
head(go_en_SARC_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_SARC, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-SARC (Unadjusted p-values)")


#make data SARCable to plots
go_plot_data <- go_en_SARC_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-SARC",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-SARC
###########################

barplot10 <- barplot(go_en_SARC, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-SARC")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r SKCM}

############################################################
#pull pvalues for SKCM 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_SKCM")

#filter pvalues < 0.05 but only to TCGA SKCM
filtered_pval_SKCM <- subset(xist_csv, TCGA.SKCM_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-SKCM
gene_list_SKCM <- filtered_pval_SKCM$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_SKCM)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# RemSKCMe version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_SKCM)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_SKCM <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_SKCM)

# make the go en into a df
go_en_SKCM_df <- as.data.frame(go_en_SKCM)

#head df
head(go_en_SKCM_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_SKCM, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-SKCM (Unadjusted p-values)")


#make data SKCMable to plots
go_plot_data <- go_en_SKCM_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-SKCM",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-SKCM
###########################

barplot10 <- barplot(go_en_SKCM, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-SKCM")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r STAD}



############################################################
#pull pvalues for STAD 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_STAD")

#filter pvalues < 0.05 but only to TCGA STAD
filtered_pval_STAD <- subset(xist_csv, TCGA.STAD_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-STAD
gene_list_STAD <- filtered_pval_STAD$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_STAD)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# RemSTADe version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_STAD)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_STAD <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_STAD)

# make the go en into a df
go_en_STAD_df <- as.data.frame(go_en_STAD)

#head df
head(go_en_STAD_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_STAD, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-STAD (Unadjusted p-values)")


#make data STADable to plots
go_plot_data <- go_en_STAD_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-STAD",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-STAD
###########################

barplot10 <- barplot(go_en_STAD, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-STAD")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r THCA}
############################################################
#pull pvalues for THCA 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_THCA")

#filter pvalues < 0.05 but only to TCGA THCA
filtered_pval_THCA <- subset(xist_csv, TCGA.THCA_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-THCA
gene_list_THCA <- filtered_pval_THCA$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_THCA)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# RemTHCAe version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_THCA)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_THCA <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_THCA)

# make the go en into a df
go_en_THCA_df <- as.data.frame(go_en_THCA)

#head df
head(go_en_THCA_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_THCA, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-THCA (Unadjusted p-values)")


#make data THCAable to plots
go_plot_data <- go_en_THCA_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-THCA",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-THCA
###########################

barplot10 <- barplot(go_en_THCA, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-THCA")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r THYM}

############################################################
#pull pvalues for THYM 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_THYM")

#filter pvalues < 0.05 but only to TCGA THYM
filtered_pval_THYM <- subset(xist_csv, TCGA.THYM_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-THYM
gene_list_THYM <- filtered_pval_THYM$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_THYM)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# RemTHYMe version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_THYM)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_THYM <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_THYM)

# make the go en into a df
go_en_THYM_df <- as.data.frame(go_en_THYM)

#head df
head(go_en_THYM_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_THYM, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-THYM (Unadjusted p-values)")


#make data THYMable to plots
go_plot_data <- go_en_THYM_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-THYM",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-THYM
###########################

barplot10 <- barplot(go_en_THYM, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-THYM")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r UCEC}

############################################################
#pull pvalues for UCEC 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_UCEC")

#filter pvalues < 0.05 but only to TCGA UCEC
filtered_pval_UCEC <- subset(xist_csv, TCGA.UCEC_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-UCEC
gene_list_UCEC <- filtered_pval_UCEC$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_UCEC)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# RemUCECe version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_UCEC)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_UCEC <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_UCEC)

# make the go en into a df
go_en_UCEC_df <- as.data.frame(go_en_UCEC)

#head df
head(go_en_UCEC_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_UCEC, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-UCEC (Unadjusted p-values)")


#make data UCECable to plots
go_plot_data <- go_en_UCEC_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-UCEC",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-UCEC
###########################

barplot10 <- barplot(go_en_UCEC, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-UCEC")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r UCS}

############################################################
#pull pvalues for UCS 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_UCS")

#filter pvalues < 0.05 but only to TCGA UCS
filtered_pval_UCS <- subset(xist_csv, TCGA.UCS_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-UCS
gene_list_UCS <- filtered_pval_UCS$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_UCS)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# RemUCSe version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_UCS)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_UCS <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_UCS)

# make the go en into a df
go_en_UCS_df <- as.data.frame(go_en_UCS)

#head df
head(go_en_UCS_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_UCS, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-UCS (Unadjusted p-values)")


#make data UCSable to plots
go_plot_data <- go_en_UCS_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-UCS",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-UCS
###########################

barplot10 <- barplot(go_en_UCS, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-UCS")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```

```{r UVM}

############################################################
#pull pvalues for UVM 

# View column names 
colnames(xist_csv)

#study name
study <- c("TCGA_UVM")

#filter pvalues < 0.05 but only to TCGA UVM
filtered_pval_UVM <- subset(xist_csv, TCGA.UVM_P.Value < 0.05)
# Extract gene list from the filtered data for TCGA-UVM
gene_list_UVM <- filtered_pval_UVM$genes

#view head of gene list of pvalues <0.05, ENS ID
head(gene_list_UVM)
###################################################################
#must clean the EID numbers, this willnot work with the ENDG00001233455.091 for example
# RemUVMe version numbers from Ensembl IDs
cleaned_gene_list <- sub("\\..*", "", gene_list_UVM)

# View the cleaned list
head(cleaned_gene_list)

# some genes will not be mapped (7.9%) because ???
unmapped_genes <- cleaned_gene_list[!cleaned_gene_list %in% gene_conversion$ENSEMBL]

# this is to see the unmapped genes
unmapped_genes

# Convert cleaned ENS to Gene Symbols
gene_conversion <- bitr(cleaned_gene_list, fromType = "ENSEMBL", 
                        toType = "SYMBOL", 
                        OrgDb = org.Hs.eg.db)

# View the converted gene symbols
head(gene_conversion)


# Proceed with the mapped genes
mapped_genes <- gene_conversion$SYMBOL

# Perform GO enrichment
go_en_UVM <- enrichGO(gene = mapped_genes,
                       OrgDb = org.Hs.eg.db,
                       keyType = "SYMBOL",
                       ont = "BP", 
                       pAdjustMethod = "BH",
                       qvalueCutoff = 1)

# View results
head(go_en_UVM)

# make the go en into a df
go_en_UVM_df <- as.data.frame(go_en_UVM)

#head df
head(go_en_UVM_df)


#######################
# bar plot creation!
#######################


# Plot the GO enrichment results using unadjusted p-values but why it still says padjust
barplot(go_en_UVM, showCategory = 10, title = "Top 10 GO Terms for XIST-loss in TCGA-UVM (Unadjusted p-values)")


#make data UVMable to plots
go_plot_data <- go_en_UVM_df %>%
  arrange(desc(Count)) %>%
  head(10)  #top 10 genes


# Create bar plot
plot <- ggplot(go_plot_data, aes(x = reorder(Description, -Count), y = Count, fill = Count)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "GO Enrichment Analysis for TCGA-UVM",
       x = "GO Terms",
       y = "Gene Count") +
  theme_minimal()

###########################
#top 10 GO terms for XIST loss in TCGA-UVM
###########################

barplot10 <- barplot(go_en_UVM, showCategory = 10, title = "Top 10 Terms for XIST-loss in TCGA-UVM")


#SAVE BARPLOTS

#output
output_dir <- "C:/Users/Owner/Documents/TCGA_GO_BAR_PLOTS/"

# Create a filename using the study name
filename <- paste0(output_dir, study, "_GO_Enrichment.png")
filename10 <- paste0(output_dir, study, "_10_GO_Enrichment.png")

# Save the plot
ggsave(filename = filename, plot = plot, width = 10, height = 8, dpi = 300)
ggsave(filename = filename10, plot = barplot10, width = 10, height = 8, dpi = 300)

```