---
title: "Sex differences in HSP genes"
author: "Luise A. Seeker"
date: "13/09/2022"
output: html_document
---

```{r}
library(Seurat)
library(dplyr)
library(here)
library(ggplot2)
library(gridExtra)
library(data.table)
library(ggvenn)
```


```{r, echo = F}
mypal <- pal_npg("nrc", alpha = 0.7)(10)
mypal2 <-pal_tron("legacy", alpha = 0.7)(7)
mypal3 <- pal_lancet("lanonc", alpha = 0.7)(9)
mypal4 <- pal_simpsons(palette = c("springfield"), alpha = 0.7)(16)
mypal5 <- pal_rickandmorty(palette = c("schwifty"), alpha = 0.7)(6)
mypal6 <- pal_futurama(palette = c("planetexpress"), alpha = 0.7)(5)
mypal7 <- pal_startrek(palette = c("uniform"), alpha = 0.7)(5)

mycoloursP<- c(mypal, mypal2, mypal3, mypal4, mypal5, mypal6, mypal7)


```

```{r}
nad_ol <-  readRDS(here("data", 
                                 "single_nuc_data", 
                                 "oligodendroglia",
                                 "srt_oligos_and_opcs_LS.RDS"))


```



Load data




Filter for opcs
```{r}

Idents(nad_ol) <- "ol_clusters_named"

opcs <- subset(nad_ol, ident = c("OPC_A", "OPC_B"))

```

Filter for oligos
```{r}

oligos <- subset(nad_ol, ident = c("OPC_A", "OPC_B", "COP_A", "COP_B", 
                                   "COP_C"), invert = TRUE)

```

```{r}
Idents(opcs) <- "gender"

sex_markopc <- FindMarkers(opcs, ident.1 = "M",
                          ident.2 = "F",
                          only.pos = FALSE,
                        test.use = "MAST")

sex_markopc$cell_type <- "opcs"

```


```{r}
Idents(oligos) <- "gender"

sex_mark_ol <- FindMarkers(oligos, ident.1 = "M",
                          ident.2 = "F",
                          only.pos = FALSE,
                        test.use = "MAST")

sex_mark_ol$cell_type <- "oligodendrocytes"

```

```{r}
oligos_sex_mark <- rbind(sex_mark_ol, sex_markopc)

```


Read in astrocyte and microglia data

```{r}
astrocytes <- read.csv(here("outs",
                            "astrocytes",
                            "sex_marker_list_astro",
                            "astro_sex_marker.csv"))
astrocytes$cell_type <- "astrocytes"

microglia <- read.csv(here("outs",
                            "microglia_macrophages",
                            "sex_marker_list_mm",
                            "mm_sex_marker.csv"))
microglia$cell_type <- "microglia"

as_micro <- rbind(astrocytes, microglia)
```

Find Heat shock genes in oligodendroglia
```{r}
hsp <- oligos_sex_mark[rownames(oligos_sex_mark) %like% "HSP", ] 
dnaj <- oligos_sex_mark[rownames(oligos_sex_mark) %like% "DNAJ", ]
cct <- oligos_sex_mark[rownames(oligos_sex_mark) %like% "CCT", ]
mmk <- oligos_sex_mark[rownames(oligos_sex_mark) %like% "MMK", ]
bbs<- oligos_sex_mark[rownames(oligos_sex_mark) %like% "BBS", ]

oligo_hsp <- rbind(hsp, dnaj)
oligo_hsp$gene <- rownames(oligo_hsp)
```


Find Heat shock genes in astrocytes and microglia
```{r}

as_micro$hsp <- ifelse(as_micro$gene %like% "HSP", "hsp", "NA")
as_micro$dnaj_am <- ifelse(as_micro$gene %like% "DNAJ", "dnaj", "NA") 
as_micro$cct_am <- ifelse(as_micro$gene %like% "CCT", "dnaj", "NA") 
as_micro$mmk_am <- ifelse(as_micro$gene %like% "MMK", "mmk", "NA")   
as_micro$bbs_am<- ifelse(as_micro$gene %like% "BBS", "bbs", "NA")   

as_micro_fil <- subset(as_micro, as_micro$hsp == "hsp")

as_micro_hsp <- data.frame(p_val = as_micro_fil$p_val,
                           avg_log2FC = as_micro_fil$avg_log2FC,
                           pct.1 = as_micro_fil$pct.1,
                           pct.2 = as_micro_fil$pct.2,
                           p_val_adj = as_micro_fil$p_val_adj,
                           gene = as_micro_fil$gene,
                           cell_type = as_micro_fil$cell_type)

out_data <- rbind(as_micro_hsp, oligo_hsp)
```



Find other genes that are expressed in more than one glia type

```{r}
ol_as_mi <- subset(oligos_sex_mark, rownames(oligos_sex_mark) %in% as_micro$gene)

```

```{r}
ol_genes <- rownames(sex_mark_ol)
opc_genes<- rownames(sex_markopc)

# the oligodendroglia data is male only and as it is a contrast between two 
#factors female data is the same with an inversed direction. I am removing the 
# female results from the other two datasets
male_as <- subset(astrocytes, astrocytes$cluster == "M")
male_mi <- subset(microglia, microglia$cluster == "M")
as_genes <- male_as$gene
mi_genes <- male_mi $gene

gene_list <- list()
gene_list[[1]] <- ol_genes
gene_list[[2]] <- opc_genes
gene_list[[3]] <- as_genes
gene_list[[4]] <- mi_genes

names(gene_list) <- c("Oligodendrocytes", "OPCs", "Astrocytes", "Microglia")
ggvenn(gene_list)
```
```{r}

fil_sex_mark_ol <- subset(sex_mark_ol, abs(sex_mark_ol$pct.1) > 0.25)
fil_sex_mark_ol <- subset(fil_sex_mark_ol, fil_sex_mark_ol$p_val_adj < 0.05)


fil_sex_mark_opc <- subset(sex_markopc, abs(sex_markopc$pct.1) > 0.25)
fil_sex_mark_opc<- subset(fil_sex_mark_opc, fil_sex_mark_opc$p_val_adj < 0.05)

ol_genes_fil <- rownames(fil_sex_mark_ol)
opc_genes_fil<- rownames(fil_sex_mark_opc)


as_genes_fil <- subset(male_as, male_as$p_val < 0.05)
mi_genes_fil <- subset(male_mi, male_mi$p_val < 0.05)

as_genes_fil <- as_genes_fil$gene
mi_genes_fil <- mi_genes_fil$gene

gene_list_fil <- list()
gene_list_fil[[1]] <- ol_genes_fil
gene_list_fil[[2]] <- opc_genes_fil
gene_list_fil[[3]] <- as_genes_fil
gene_list_fil[[4]] <- mi_genes_fil

names(gene_list_fil) <- c("Oligodendrocytes", "OPCs", "Astrocytes", "Microglia")
ggvenn(gene_list_fil)
```


Intersect genes
```{r}
intersect(gene_list_fil[[1]], intersect(gene_list_fil[[2]], intersect(gene_list_fil[[3]], gene_list[[4]])))
```


Session info

```{r}

sessionInfo()
```