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Figure4D_pct_expressed.Rmd
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Figure4D_pct_expressed.Rmd
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---
title: "Script to calculate heatmap of percent expressed cells."
author: "Neerja Katiyar"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output: workflowr::wflow_html
editor_options:
chunk_output_type: console
---
### Prepare the environment
```{r setup, include=FALSE}
require(knitr)
knitr::opts_chunk$set(echo = TRUE)
opts_knit$set(root.dir = "/Users/katiyn/Dropbox (JAX)/MouseAging_clean/Mice_aging_NK_resubmission/code/") #set root dir!
```
```{r libraries, include=TRUE, echo=TRUE}
library(ggpubr)
library(pheatmap)
library(tidyr)
library(Seurat)
library(RColorBrewer)
```
```{r read_tabula_muris_data, include=TRUE, echo=TRUE}
spleen.subset <- readRDS("./data/spleen_seurat_subset_rename_ident_Oct24.rds")
cell.types <- unique(Idents(spleen.subset))
spleen.subset$cluster_name <- Idents(spleen.subset)
cell.types <- unique(Idents(spleen.subset))
```
### Generate heatmap for percent of cells expressing Fosb.
```{r heatmap_Fosb, include=TRUE, echo=TRUE}
df_combined <- data.frame()
for (i in cell.types) {
print(i)
data_celltype <- subset(spleen.subset@meta.data, cluster_name == i)
spleen.subset_celltype <- subset(spleen.subset, ident = i)
spleen_subset_celltype_young <- subset(spleen.subset_celltype, age == "3m")
spleen_subset_celltype_old <- subset(spleen.subset_celltype, age == "18m")
spleen_subset_celltype_young_gene <- subset(spleen_subset_celltype_young, Fosb > 0)
spleen_subset_celltype_old_gene <- subset(spleen_subset_celltype_old, Fosb > 0)
spleen_subset_celltype_young_gene_pct <- ncol(spleen_subset_celltype_young_gene)/ncol(spleen_subset_celltype_young)
spleen_subset_celltype_old_gene_pct <- ncol(spleen_subset_celltype_old_gene)/ncol(spleen_subset_celltype_old)
age_table <- data.frame(Young = spleen_subset_celltype_young_gene_pct, Aged = spleen_subset_celltype_old_gene_pct)
rownames(age_table) = i
df_combined <- rbind(df_combined, age_table)
}
print(df_combined)
df_mat <- as.matrix(df_combined)
pheatmap.val <- df_mat
breaksList = seq(0, max(pheatmap.val*100), by = .001)
gene = "Fosb"
print(gene)
pdf(paste0("./output/Pheatmap_new_cell_type_vs_age_", gene, ".pdf"), width = 4)
pheatmap::pheatmap(pheatmap.val * 100, cluster_cols = FALSE, cluster_rows = FALSE,
color = colorRampPalette((brewer.pal(n = 9, name = "Blues")))(length(breaksList)),
breaks = breaksList, border_color = "white", main = gene, display_numbers = T,
fontsize_number = 9,
number_color = "white", legend = F)
dev.off()
```
### Generate heatmap for percent of cells expressing Fos.
```{r heatmap_Fos, include=TRUE, echo=TRUE}
df_combined <- data.frame()
for (i in cell.types) {
data_celltype <- subset(spleen.subset@meta.data, cluster_name == i)
spleen.subset_celltype <- subset(spleen.subset, ident = i)
spleen_subset_celltype_young <- subset(spleen.subset_celltype, age == "3m")
spleen_subset_celltype_old <- subset(spleen.subset_celltype, age == "18m")
spleen_subset_celltype_young_gene <- subset(spleen_subset_celltype_young, Fos > 0)
spleen_subset_celltype_old_gene <- subset(spleen_subset_celltype_old, Fos > 0)
spleen_subset_celltype_young_gene_pct <- ncol(spleen_subset_celltype_young_gene)/ncol(spleen_subset_celltype_young)
spleen_subset_celltype_old_gene_pct <- ncol(spleen_subset_celltype_old_gene)/ncol(spleen_subset_celltype_old)
age_table <- data.frame(Young = spleen_subset_celltype_young_gene_pct, Aged = spleen_subset_celltype_old_gene_pct)
rownames(age_table) = i
print(age_table)
df_combined <- rbind(df_combined, age_table)
}
print(df_combined)
df_mat <- as.matrix(df_combined)
pheatmap.val <- df_mat
breaksList = seq(0, max(pheatmap.val*100), by = .001)
gene = "Fos"
print(gene)
pdf(paste0("./output/Pheatmap_new_cell_type_vs_age_", gene, ".pdf"), width = 4)
pheatmap::pheatmap(pheatmap.val * 100, cluster_cols = FALSE, cluster_rows = FALSE,
color = colorRampPalette((brewer.pal(n = 9, name = "Blues")))(length(breaksList)),
breaks = breaksList, border_color = "white", main = gene, display_numbers = T,
fontsize_number = 9,
number_color = "white", legend = F)
dev.off()
```
### Generate heatmap for percent of cells expressing Jun.
```{r heatmap_Jun, include=TRUE, echo=TRUE}
df_combined <- data.frame()
for (i in cell.types) {
data_celltype <- subset(spleen.subset@meta.data, cluster_name == i)
spleen.subset_celltype <- subset(spleen.subset, ident = i)
spleen_subset_celltype_young <- subset(spleen.subset_celltype, age == "3m")
spleen_subset_celltype_old <- subset(spleen.subset_celltype, age == "18m")
spleen_subset_celltype_young_gene <- subset(spleen_subset_celltype_young, Jun > 0)
spleen_subset_celltype_old_gene <- subset(spleen_subset_celltype_old, Jun > 0)
spleen_subset_celltype_young_gene_pct <- ncol(spleen_subset_celltype_young_gene)/ncol(spleen_subset_celltype_young)
spleen_subset_celltype_old_gene_pct <- ncol(spleen_subset_celltype_old_gene)/ncol(spleen_subset_celltype_old)
age_table <- data.frame(Young = spleen_subset_celltype_young_gene_pct, Aged = spleen_subset_celltype_old_gene_pct)
rownames(age_table) = i
print(age_table)
df_combined <- rbind(df_combined, age_table)
}
print(df_combined)
df_mat <- as.matrix(df_combined)
pheatmap.val <- df_mat
breaksList = seq(0, max(pheatmap.val*100), by = .001)
gene = "Jun"
print(gene)
pdf(paste0("./output/Pheatmap_new_cell_type_vs_age_", gene, ".pdf"), width = 4)
pheatmap::pheatmap(pheatmap.val * 100, cluster_cols = FALSE, cluster_rows = FALSE,
color = colorRampPalette((brewer.pal(n = 9, name = "Blues")))(length(breaksList)),
breaks = breaksList, border_color = "white", main = gene, display_numbers = T,
fontsize_number = 9,
number_color = "white", legend = F)
dev.off()
```