---
title: "27-heatmaps"
output: html_document
date: "2025-04-21"
---

Rmd to make heatmaps of genes contributing to the top 9 enriched biological processes across all individuals to look at expression patterns. 

### Load packages
```{r}
library(dplyr)
library(tidyverse)
library(pheatmap)
library(data.table)
library(RColorBrewer)
```

## Read in files: 
### ubiquitin-dependent protein catabolic process 
```{r}
ubiqdep <- read.csv("../analyses/27-heatmaps/uniq-dep-prot-cat_genes_counts.csv")
head(ubiqdep)
```

Select columns for heatmap:     
Gene Names and counts for each library:     
```{r}
ubiqheat <- select(ubiqdep, "gene_id", "PSC.56", "PSC.52", "PSC.54", "PSC.61","PSC.64", "PSC.73", "PSC.76", "PSC.81", "PSC.59", "PSC.57", "PSC.69", "PSC.67", "PSC.71", "PSC.75", "PSC.78", "PSC.83", "PSC.0228", "PSC.0187", "PSC.0188", "PSC.0174", "PSC.0190", "PSC.0231", "PSC.0230", "PSC.0219", "PSC.0177", "PSC.0186", "PSC.0209", "PSC.0203")
ubiqheat
```

Set heatmap colors:
```{r}
heatmapBrBG <- RColorBrewer::brewer.pal(11, "BrBG")
```



Have to make gene_id column into rownames:
Set as row names:
```{r}
rownames(ubiqheat) <- ubiqheat$gene_id #set gene IDs as rownames
ubiqheat <- ubiqheat[,-1] #remove redundant column
head(ubiqheat)
```
Create an annotation for the libraries: 
Add column annotations for the samples denoting age, and treatment  :
```{r}
sample_col <- data.frame(age = c("adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult" ,"adult", "adult", "adult", "adult", "adult", "juvenile", "juvenile", "juvenile", "adult", "adult", "adult", "juvenile", "juvenile", "juvenile", "adult", "adult", "adult"))
#add infection status info:
sample_col$treatment <- c("Control", "Control", "Control", "Control", "Control", "Control", "Control", "Control", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Control", "Control", "Control", "Control", "Control", "Control")

row.names(sample_col) <-colnames(ubiqheat)
sample_col
```

```{r}
ann_colors <- list(
  age = c("juvenile" = "#7570B3", "adult" = "#708238"), 
  treatment = c("Control" = "#E7298A","Exposed" = "#D95F02")
)
```

```{r}
pheatmap(ubiqheat, scale = "row", cluster_row = TRUE, cluster_cols = FALSE, clustering_distance_rows = "euclidean", clustering_method = "average", show_rownames = TRUE, show_colnames = TRUE, treeheight_col = 300, annotation_colors = ann_colors, annotation_col = sample_col, legend = TRUE, color = heatmapBrBG, fontsize_col = 12, fontsize_row = 12)

```

Save heatmap to analyses/pheatmap:
```{r}
pdf("../analyses/27-heatmaps/ubiq-dep-prot-cat-proc-heatmap.pdf", width = 11, height = 8.5)
pheatmap(ubiqheat, scale = "row", cluster_row = TRUE, cluster_cols = FALSE, clustering_distance_rows = "euclidean", clustering_method = "average", show_rownames = TRUE, show_colnames = TRUE, treeheight_col = 300, annotation_colors = ann_colors, annotation_col = sample_col, legend = TRUE, color = heatmapBrBG, fontsize_col = 12, fontsize_row = 12)
dev.off()
```

### tumor-necrosis factor-mediated signaling pathway 
```{r}
tumor <- read.csv("../analyses/27-heatmaps/tumor-nec-fac-med-path_gene_counts.csv")
head(tumor)
```

Select columns for heatmap:     
Gene Names and counts for each library:     
```{r}
tumorheat <- select(tumor, "gene_id", "PSC.56", "PSC.52", "PSC.54", "PSC.61","PSC.64", "PSC.73", "PSC.76", "PSC.81", "PSC.59", "PSC.57", "PSC.69", "PSC.67", "PSC.71", "PSC.75", "PSC.78", "PSC.83", "PSC.0228", "PSC.0187", "PSC.0188", "PSC.0174", "PSC.0190", "PSC.0231", "PSC.0230", "PSC.0219", "PSC.0177", "PSC.0186", "PSC.0209", "PSC.0203")
tumorheat
```

Set heatmap colors:
```{r}
heatmapBrBG <- RColorBrewer::brewer.pal(11, "BrBG")
```

Have to make gene_id column into rownames:
Set as row names:
```{r}
rownames(tumorheat) <- tumorheat$gene_id #set gene IDs as rownames
tumorheat <- tumorheat[,-1] #remove redundant column
head(tumorheat)
```
Create an annotation for the libraries: 
Add column annotations for the samples denoting age, and treatment  :
```{r}
sample_col <- data.frame(age = c("adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult" ,"adult", "adult", "adult", "adult", "adult", "juvenile", "juvenile", "juvenile", "adult", "adult", "adult", "juvenile", "juvenile", "juvenile", "adult", "adult", "adult"))
#add infection status info:
sample_col$treatment <- c("Control", "Control", "Control", "Control", "Control", "Control", "Control", "Control", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Control", "Control", "Control", "Control", "Control", "Control")

row.names(sample_col) <-colnames(tumorheat)
sample_col
```

```{r}
ann_colors <- list(
  age = c("juvenile" = "#7570B3", "adult" = "#708238"), 
  treatment = c("Control" = "#E7298A","Exposed" = "#D95F02")
)
```

```{r}
pheatmap(tumorheat, scale = "row", cluster_row = TRUE, cluster_cols = FALSE, clustering_distance_rows = "euclidean", clustering_method = "average", show_rownames = TRUE, show_colnames = TRUE, treeheight_col = 300, annotation_colors = ann_colors, annotation_col = sample_col, legend = TRUE, color = heatmapBrBG, fontsize_col = 12, fontsize_row = 12)

```

Save heatmap to analyses/pheatmap:
```{r}
pdf("../analyses/27-heatmaps/tumor-nec-fact-med-sig-path-heatmap.pdf", width = 11, height = 8.5)
pheatmap(tumorheat, scale = "row", cluster_row = TRUE, cluster_cols = FALSE, clustering_distance_rows = "euclidean", clustering_method = "average", show_rownames = TRUE, show_colnames = TRUE, treeheight_col = 300, annotation_colors = ann_colors, annotation_col = sample_col, legend = TRUE, color = heatmapBrBG, fontsize_col = 12, fontsize_row = 12)
dev.off()
```

# CLEAR ENVIRONMENT
## defense response to bacterium 
```{r}
bacterium <- read.csv("../analyses/27-heatmaps/defense-to-bacterium_genes_counts.csv")
head(bacterium)
```
Select columns for heatmap:     
Gene Names and counts for each library:     
```{r}
bacterium <- select(bacterium, "gene_id", "PSC.56", "PSC.52", "PSC.54", "PSC.61","PSC.64", "PSC.73", "PSC.76", "PSC.81", "PSC.59", "PSC.57", "PSC.69", "PSC.67", "PSC.71", "PSC.75", "PSC.78", "PSC.83", "PSC.0228", "PSC.0187", "PSC.0188", "PSC.0174", "PSC.0190", "PSC.0231", "PSC.0230", "PSC.0219", "PSC.0177", "PSC.0186", "PSC.0209", "PSC.0203")
bacterium
```

Set heatmap colors:
```{r}
heatmapBrBG <- RColorBrewer::brewer.pal(11, "BrBG")
```

Have to make gene_id column into rownames:
Set as row names:
```{r}
rownames(bacterium) <- bacterium$gene_id #set gene IDs as rownames
bacterium <- bacterium[,-1] #remove redundant column
head(bacterium)
```
Create an annotation for the libraries: 
Add column annotations for the samples denoting age, and treatment  :
```{r}
sample_col <- data.frame(age = c("adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult", "adult" ,"adult", "adult", "adult", "adult", "adult", "juvenile", "juvenile", "juvenile", "adult", "adult", "adult", "juvenile", "juvenile", "juvenile", "adult", "adult", "adult"))
#add infection status info:
sample_col$treatment <- c("Control", "Control", "Control", "Control", "Control", "Control", "Control", "Control", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Exposed", "Control", "Control", "Control", "Control", "Control", "Control")

row.names(sample_col) <-colnames(bacterium)
sample_col
```

```{r}
ann_colors <- list(
  age = c("juvenile" = "#7570B3", "adult" = "#708238"), 
  treatment = c("Control" = "#E7298A","Exposed" = "#D95F02")
)
```

```{r}
pheatmap(bacterium, scale = "row", cluster_row = TRUE, cluster_cols = FALSE, clustering_distance_rows = "euclidean", clustering_method = "average", show_rownames = TRUE, show_colnames = TRUE, treeheight_col = 300, annotation_colors = ann_colors, annotation_col = sample_col, legend = TRUE, color = heatmapBrBG, fontsize_col = 12, fontsize_row = 12)

```

Save heatmap to analyses/pheatmap:
```{r}
pdf("../analyses/27-heatmaps/defense-response-to-bacterium-heatmap.pdf", width = 11, height = 8.5)
pheatmap(bacterium, scale = "row", cluster_row = TRUE, cluster_cols = FALSE, clustering_distance_rows = "euclidean", clustering_method = "average", show_rownames = TRUE, show_colnames = TRUE, treeheight_col = 300, annotation_colors = ann_colors, annotation_col = sample_col, legend = TRUE, color = heatmapBrBG, fontsize_col = 12, fontsize_row = 12)
dev.off()
```