---
title: "combine_val_data_cluster"
author: "Luise A. Seeker"
date: "01/09/2022"
output: html_document
---
# Introduction
With this script I am plotting co-expression of marker genes in the snRNAseq and
validation datasets.
N.B. This scipts takes variables from my environment.
```{r}
library(gridExtra)
```
Take objects from environment and re-name
1) SPARC OPALIN
```{r}
SPARC_opalin_olig2
#sparc_opalin_long <- long_data
sparc_opalin_seq <- subs_df_snrna_seq
sparc_opalin_seq$marker <- ifelse(sparc_opalin_seq$gene_expr == "SPARC+", "Marker1+",
ifelse(sparc_opalin_seq$gene_expr == "OPALIN+",
"Marker2+", "Double+"))
sparc_opalin_seq$marker <- factor(sparc_opalin_seq$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
sparc_opalin_seq$colabel <- "SPARC OPALIN"
```
2) SPARC RBFOX1
```{r}
sparc_rbfox1_seq <- subs_data
sparc_rbfox1_seq$marker <- ifelse(sparc_rbfox1_seq$gene_expr == "SPARC+", "Marker1+",
ifelse(sparc_rbfox1_seq$gene_expr == "RBFOX1+",
"Marker2+", "Double+"))
sparc_rbfox1_seq$marker <- factor(sparc_rbfox1_seq$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
sparc_rbfox1_seq$colabel <- "SPARC RBFOX1"
# IF data
sp_rb_prot <- sort_red_long
```
3) OPALIN RBFOX1
```{r}
opalin_rbfox1_seq <- subs_df_snrna_seq
opalin_rbfox1_seq$marker <- ifelse(opalin_rbfox1_seq$gene_expr == "OPALIN+", "Marker1+",
ifelse(opalin_rbfox1_seq$gene_expr == "RBFOX1+",
"Marker2+", "Double+"))
opalin_rbfox1_seq$marker <- factor(opalin_rbfox1_seq$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
opalin_rbfox1_seq$colabel <- "OPALIN RBFOX1"
```
4)
```{r}
#FMN1 RBFOX1 data
fmn1_rbfox1
head(subs_subs_data)
# complete long_data inclduding all quantified cells
#fmn1_rbfox1_long <- long_data
#FMN1 RBFOX1 snRNAseq
fmn1_rbfox1_seq <- subs_df_snrna_seq
fmn1_rbfox1_seq$marker <- ifelse(fmn1_rbfox1_seq$gene_expr == "FMN1+", "Marker1+",
ifelse(fmn1_rbfox1_seq$gene_expr == "RBFOX1+",
"Marker2+", "Double+"))
fmn1_rbfox1_seq$marker <- factor(fmn1_rbfox1_seq$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
fmn1_rbfox1_seq$colabel <- "FMN1 RBFOX1"
```
5)
```{r}
# SPARC HCN2 snRNAseq
sp_hc_seq <- subs_data
sp_hc_seq$marker <- ifelse(sp_hc_seq$gene_expr == "SPARC+", "Marker1+",
ifelse(sp_hc_seq$gene_expr == "HCN2+",
"Marker2+", "Double+"))
sp_hc_seq$marker <- factor(sp_hc_seq$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
sp_hc_seq$colabel <- "SPARC HCN2"
```
6)
```{r}
# NELL1 PAX3 snRNAseq
ne_pa_seq <- subs_data
ne_pa_seq$marker <- ifelse(ne_pa_seq$gene_expr == "NELL1+", "Marker1+",
ifelse(ne_pa_seq$gene_expr == "PAX3+",
"Marker2+", "Double+"))
ne_pa_seq$marker <- factor(ne_pa_seq$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
ne_pa_seq$colabel <- "NELL1 PAX3"
```
```{r}
snRNAseq <- rbind(sparc_opalin_seq,
fmn1_rbfox1_seq,
sparc_rbfox1_seq,
opalin_rbfox1_seq)
snRNAseq <- rbind(snRNAseq[,2:6],
sp_hc_seq)
snRNAseq <- rbind(snRNAseq,
ne_pa_seq)
```
```{r}
snRNAseq$colabel <- factor(snRNAseq$colabel,
levels = c("SPARC OPALIN",
"SPARC RBFOX1",
"OPALIN RBFOX1",
"FMN1 RBFOX1",
"SPARC HCN2",
"NELL1 PAX3"))
snRNAseq$marker <- factor(snRNAseq$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
p11 <- ggplot(snRNAseq, aes(x = colabel, y=percentage, fill = marker))+
geom_bar(stat="identity", position = "fill")+
scale_fill_manual(values= mycoloursP[24:50]) +
ylab("Proportion")+
xlab("") +
theme_minimal()+
theme(axis.text.x = element_text(angle = -90))
p11
```
```{r}
write.csv(snRNAseq, here("data",
"validation_data",
"snRNAseq_ol_clust_mark_coexpression.csv"))
```
# combine validation data
```{r}
# prepare sparc opalin olig2 IF data
sp_op_prep <- data.frame(sample_id = sparc_opalin_long$sample_id,
donor_id = sparc_opalin_long$donor_id,
Tissue = sparc_opalin_long$tissue,
keycol = sparc_opalin_long$keycol,
valuecol= sparc_opalin_long$valuecol)
sp_op_prep$marker <- ifelse(sp_op_prep$keycol == "Num_SPARC_OLIG2",
"Marker1+",
ifelse(sp_op_prep$keycol == "Num_OLIG2_OPALIN",
"Marker2+",
ifelse(sp_op_prep$keycol == "Num_SPARC_OLIG2_OPALIN",
"Double+", "exclude")))
subs_sd_op <- subset(sp_op_prep, sp_op_prep$marker != "exclude")
subs_sd_op$marker <- as.factor(subs_sd_op$marker)
subs_sd_op$marker <- factor(subs_sd_op$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
subs_sd_op$colabel <- "SPARC OPALIN OLIG2"
# prepare SPARC RNFOX1 OLIF2 IF data
sp_rb_prep <- data.frame(sample_id = sp_rb_prot$sample_id,
donor_id = sp_rb_prot$donor_id,
Tissue = sp_rb_prot$tissue,
keycol = sp_rb_prot$keycol,
valuecol= sp_rb_prot$valuecol)
sp_rb_prep$marker <- ifelse(sp_rb_prep$keycol == "Num_SPARC_OLIG2",
"Marker1+",
ifelse(sp_rb_prep$keycol == "Num_RBFOX1_OLIG2",
"Marker2+",
ifelse(sp_rb_prep$keycol == "Num_RBFOX1_SPARC_OLIG2",
"Double+", "exclude")))
subs_sp_rb <- subset(sp_rb_prep, sp_rb_prep$marker != "exclude")
subs_sp_rb$marker <- as.factor(subs_sp_rb$marker)
subs_sp_rb$marker <- factor(subs_sp_rb$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
subs_sp_rb$colabel <- "SPARC RBFOX1 OLIG2"
# prepare OPALIN RBFOX1 OLIG2 IF data
op_rb_prot <- long_data
op_rb_prep <- data.frame(sample_id = op_rb_prot$sample_id,
donor_id = op_rb_prot$donor_id,
Tissue = op_rb_prot$tissue,
keycol = op_rb_prot$keycol,
valuecol= op_rb_prot$valuecol)
op_rb_prep$marker <- ifelse(op_rb_prep$keycol == "Num_OPALIN_OLIG2",
"Marker1+",
ifelse(op_rb_prep$keycol == "Num_OLIG2_RBFOX1",
"Marker2+",
ifelse(op_rb_prep$keycol == "Num.OPALIN..OLIG2..RBFOX1",
"Double+", "exclude")))
op_rb_prep <- subset(op_rb_prep, op_rb_prep$marker != "exclude")
op_rb_prep$marker <- factor(op_rb_prep$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
op_rb_prep$colabel <- "OPALIN RBFOX1 OLIG2"
# prepare FMN1 RBFOX1 OLIG2 IF data
fm_rb_prep <- data.frame(sample_id = fmn1_rbfox1_long$sample_id,
donor_id = fmn1_rbfox1_long$donor_id,
Tissue = fmn1_rbfox1_long$tissue,
keycol = fmn1_rbfox1_long$keycol,
valuecol= fmn1_rbfox1_long$valuecol)
fm_rb_prep$marker <- ifelse(fmn1_rbfox1_long$keycol == "FMN1_OLIG2",
"Marker1+",
ifelse(fm_rb_prep$keycol == "RBFOX1_OLIG2",
"Marker2+",
ifelse(fm_rb_prep$keycol == "FMN1_RBFOX1_OLIG2",
"Double+", "exclude")))
subs_fm_rb <- subset(fm_rb_prep, fm_rb_prep$marker != "exclude")
subs_fm_rb$marker <- factor(subs_fm_rb$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
subs_fm_rb$colabel <- "FMN1 RBFOX1 OLIG2"
# prepare SPARC HCN2 data
sp_hc_long <- long_data
sp_hc_long$donor_id <- substr(sp_hc_long$sample_id, 1,8)
sp_hc_prep <- data.frame(sample_id = sp_hc_long$sample_id,
donor_id = sp_hc_long$donor_id,
Tissue = sp_hc_long$tissue,
keycol = sp_hc_long$keycol,
valuecol= sp_hc_long$valuecol)
sp_hc_prep$marker <- ifelse(sp_hc_prep$keycol == "Num_OLIG2_SPARC",
"Marker1+",
ifelse(sp_hc_prep$keycol == "Num_OLIG2_HCN2",
"Marker2+",
ifelse(sp_hc_prep$keycol == "Num_OLIG2_SPARC_HCN2",
"Double+", "exclude")))
sp_hc_prep <- subset(sp_hc_prep, sp_hc_prep$marker != "exclude")
sp_hc_prep$marker <- factor(sp_hc_prep$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
sp_hc_prep$colabel <- "SPARC HCN2 OLIG2"
# NELL1 PDGFRA
ne_pd_long <- long_data
ne_pd_long$donor_id <- paste(substr(ne_pd_long$sample_id, 1,8))
ne_pd_long$tissue <- substr(ne_pd_long$sample_id, 10,12)
ne_pd_long <- data.frame(sample_id = ne_pd_long$sample_id,
donor_id = ne_pd_long$donor_id,
Tissue = ne_pd_long$tissue,
keycol = ne_pd_long$keycol,
valuecol= ne_pd_long$valuecol)
ne_pd_long$marker <- ifelse(ne_pd_long$keycol == "NELL1_C2",
"Marker1+",
ifelse(ne_pd_long$keycol == "PDRFRA_C1",
"Marker2+",
ifelse(ne_pd_long$keycol == "PDGFRA_NELL1",
"Double+", "exclude")))
ne_pd_long <- subset(ne_pd_long, ne_pd_long$marker != "exclude")
ne_pd_long$marker <- factor(ne_pd_long$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
ne_pd_long$colabel <- "NELL1 PDGFRA"
# PAX3 PDGFRA
pa_pd_long <- long_data
#pa_pd_long$donor_id <- paste(substr(pa_pd_long$sample_id, 1,8))
#pa_pd_long$tissue <- substr(pa_pd_long$sample_id, 10,12)
pa_pdprep <- data.frame(sample_id = pa_pd_long$sample_id,
donor_id = pa_pd_long$donor_id,
Tissue = pa_pd_long$tissue,
keycol = pa_pd_long$keycol,
valuecol= pa_pd_long$valuecol)
pa_pdprep$marker <- ifelse(pa_pdprep$keycol == "PAX3_pos",
"Marker1+",
ifelse(pa_pdprep$keycol == "PDGFRA_pos",
"Marker2+",
ifelse(pa_pdprep$keycol == "double_pos",
"Double+", "exclude")))
pa_pdprep <- subset(pa_pdprep, pa_pdprep$marker != "exclude")
pa_pdprep$marker <- factor(pa_pdprep$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
pa_pdprep$colabel <- "PAX3 PDGFRA"
```
# combine datasets
```{r}
#prot_data <- rbind(subs_sd_op, subs_fm_rb, subs_sp_rb, op_rb_prep)
#prot_data <- rbind(prot_data[,2:8],sp_hc_prep)
prot_data <- rbind(prot_data,pa_pdprep)
prot_data$colabel <- factor(prot_data$colabel,
levels = c("SPARC OPALIN OLIG2",
"SPARC RBFOX1 OLIG2",
"OPALIN RBFOX1 OLIG2",
"FMN1 RBFOX1 OLIG2",
"SPARC HCN2 OLIG2",
"NELL1 PDGFRA",
"PAX3 PDGFRA"))
prot_data$marker <- factor(prot_data$marker, levels = c("Marker1+",
"Double+", "Marker2+"))
p1 <- ggplot(prot_data, aes(x = colabel, y=valuecol, fill = marker))+
geom_bar(stat="identity", position = "fill")+
scale_fill_manual(values= mycoloursP[24:50]) +
ylab("Proportion")+
xlab("") +
theme_minimal()+
theme(axis.text.x = element_text(angle = -90))
p1
bool_pax3 <- prot_data$colabel == "PAX3 PDGFRA" &
prot_data$marker == "Marker1+"
subs_prot <- prot_data[!bool_pax3,]
bool_nell1 <- subs_prot$colabel == "NELL1 PDGFRA" &
subs_prot$marker == "Marker1+"
subs_prot_2 <- subs_prot[!bool_nell1,]
p2 <- ggplot(subs_prot_2, aes(x = colabel, y=valuecol, fill = marker))+
geom_bar(stat="identity", position = "fill")+
scale_fill_manual(values= mycoloursP[24:50]) +
ylab("Proportion")+
xlab("") +
theme_minimal()+
theme(axis.text.x = element_text(angle = -90))
p2
```
```{r}
grid.arrange(p11, p1, ncol = 2)
```
```{r}
write.csv(prot_data, here("data",
"validation_data",
"IF_ol_clust_mark_coexpression.csv"))
```
```{r}
Idents(nad_ol) <- "ol_clusters_named"
oligos <- subset(nad_ol, idents = c("Oligo_A",
"Oligo_B",
"Oligo_C",
"Oligo_D",
"Oligo_E",
"Oligo_F"))
opcs <- subset(nad_ol, idents = c("OPC_A", "OPC_B"))
Idents(opcs) <- "Tissue"
ba4_opcs <-subset(opcs, idents = "BA4")
cb_opcs <-subset(opcs, idents = "CB")
csc_opcs <-subset(opcs, idents = "CSC")
NELL1 <- 'NELL1'
PDGFRA <- 'PDGFRA'
NELL1.cutoff <- 1
PDGFRA.cutoff <- 1
#BA4
NELL1_cells_ba4 <- length(which(FetchData(ba4_opcs, vars = NELL1) > NELL1.cutoff &
FetchData(ba4_opcs, vars = PDGFRA) < PDGFRA.cutoff))
PDGFRA_cells_ba4 <- length(which(FetchData(ba4_opcs, vars = PDGFRA) > PDGFRA.cutoff &
FetchData(ba4_opcs, vars = NELL1) < NELL1.cutoff))
NELL1_PDGFRA_olig2_cells_ba4 <- length(which(FetchData(ba4_opcs, vars = PDGFRA) > PDGFRA.cutoff &
FetchData(ba4_opcs, vars = NELL1) > NELL1.cutoff))
all_cells_incluster_ba4 <- table(ba4_opcs@active.ident)
NELL1_ba4 <-NELL1_cells_ba4/all_cells_incluster_ba4 * 100
# Percentage of cells in dataset that express NELL1
PDGFRA_ba4 <- PDGFRA_cells_ba4/all_cells_incluster_ba4 * 100
#Percentage of cells in dataset that express PDGFRA
double_ba4 <- NELL1_PDGFRA_olig2_cells_ba4/all_cells_incluster_ba4 * 100
#Percentage of cells in dataset that co-express NELL1 + PDGFRA
#CB
NELL1_cells_cb <- length(which(FetchData(cb_opcs, vars = NELL1) > NELL1.cutoff &
FetchData(cb_opcs, vars = PDGFRA) < PDGFRA.cutoff))
PDGFRA_cells_cb <- length(which(FetchData(cb_opcs, vars = PDGFRA) > PDGFRA.cutoff&
FetchData(cb_opcs, vars = NELL1) < NELL1.cutoff))
NELL1_PDGFRA_olig2_cells_cb <- length(which(FetchData(cb_opcs, vars = PDGFRA) >
PDGFRA.cutoff & FetchData(cb_opcs, vars = NELL1) >
NELL1.cutoff))
all_cells_incluster_cb <- table(cb_opcs@active.ident)
NELL1_cb <- NELL1_cells_cb/all_cells_incluster_cb * 100 # Percentage of cells in dataset that express NELL1
PDGFRA_cb <- PDGFRA_cells_cb/all_cells_incluster_cb * 100 #Percentage of cells in dataset that express PDGFRA
double_cb <- NELL1_PDGFRA_olig2_cells_cb/all_cells_incluster_cb * 100 #Percentage of cells in dataset that co-express NELL1 + PDGFRA
#CSC
NELL1_cells_csc <- length(which(FetchData(csc_opcs, vars = NELL1) > NELL1.cutoff&
FetchData(csc_opcs, vars = PDGFRA) < PDGFRA.cutoff))
PDGFRA_cells_csc <- length(which(FetchData(csc_opcs, vars = PDGFRA) > PDGFRA.cutoff &
FetchData(csc_opcs, vars = NELL1) < NELL1.cutoff))
NELL1_PDGFRA_olig2_cells_csc <- length(which(FetchData(csc_opcs, vars = PDGFRA) >
PDGFRA.cutoff & FetchData(csc_opcs, vars = NELL1) >
NELL1.cutoff))
all_cells_incluster_csc <- table(csc_opcs@active.ident)
NELL1_csc <- NELL1_cells_csc/all_cells_incluster_csc * 100
# Percentage of cells in dataset that express NELL1
PDGFRA_csc <- PDGFRA_cells_csc/all_cells_incluster_csc * 100
#Percentage of cells in dataset that express PDGFRA
double_csc <- NELL1_PDGFRA_olig2_cells_csc/all_cells_incluster_csc * 100
#Percentage of cells in dataset that co-express NELL1 + PDGFRA
df_snrna_seq <- data.frame(Tissue = c(rep("BA4", 4),
rep("CB", 4),
rep("CSC", 4)),
gene_expr = rep(c("NELL1+",
"PDGFRA+",
"NELL1+PDGFRA+",
"Other OPCs"), 3),
percentage = c(as.numeric(NELL1_ba4),
as.numeric(PDGFRA_ba4),
as.numeric(double_ba4),
100 - (as.numeric(NELL1_ba4)+
as.numeric(PDGFRA_ba4)+
as.numeric(double_ba4)),
as.numeric(NELL1_cb),
as.numeric(PDGFRA_cb),
as.numeric(double_cb),
100 - (as.numeric(NELL1_cb)+
as.numeric(PDGFRA_cb)+
as.numeric(double_cb)),
as.numeric(NELL1_csc),
as.numeric(PDGFRA_csc),
as.numeric(double_csc),
100 - (as.numeric(NELL1_csc)+
as.numeric(PDGFRA_csc)+
as.numeric(double_csc))))
ggplot(df_snrna_seq, aes(x = Tissue, y=percentage, fill = gene_expr))+
geom_bar(stat="identity")+scale_fill_manual(values= mycoloursP[24:50])
subs_data <- subset(df_snrna_seq, df_snrna_seq$gene_expr != "Other OPCs")
ggplot(subs_data, aes(x = Tissue, y=percentage, fill = gene_expr))+
geom_bar(stat="identity")+scale_fill_manual(values= mycoloursP[24:50])
ggplot(subs_data, aes(x = Tissue, y=percentage, fill = gene_expr))+
geom_bar(stat="identity", position = "fill")+scale_fill_manual(values= mycoloursP[24:50])
```
```{r}
nell1_data <- subs_data
nell1_data$coexpr <- "NELL1 PDGFRA"
nell1_data$marker <- ifelse(nell1_data$gene_expr == "NELL1+", "Marker1+",
ifelse(nell1_data$gene_expr == "PDGFRA+", "PDGFRA+",
"Double+"))
```
PAX3 OPCs
```{r}
PAX3 <- 'PAX3'
PDGFRA <- 'PDGFRA'
PAX3.cutoff <- 1
PDGFRA.cutoff <- 1
#BA4
PAX3_cells_ba4 <- length(which(FetchData(ba4_opcs, vars = PAX3) > PAX3.cutoff &
FetchData(ba4_opcs, vars = PDGFRA) < PDGFRA.cutoff))
PDGFRA_cells_ba4 <- length(which(FetchData(ba4_opcs, vars = PDGFRA) > PDGFRA.cutoff &
FetchData(ba4_opcs, vars = PAX3) < PAX3.cutoff))
PAX3_PDGFRA_olig2_cells_ba4 <- length(which(FetchData(ba4_opcs, vars = PDGFRA) > PDGFRA.cutoff &
FetchData(ba4_opcs, vars = PAX3) > PAX3.cutoff))
all_cells_incluster_ba4 <- table(ba4_opcs@active.ident)
PAX3_ba4 <-PAX3_cells_ba4/all_cells_incluster_ba4 * 100
# Percentage of cells in dataset that express PAX3
PDGFRA_ba4 <- PDGFRA_cells_ba4/all_cells_incluster_ba4 * 100
#Percentage of cells in dataset that express PDGFRA
double_ba4 <- PAX3_PDGFRA_olig2_cells_ba4/all_cells_incluster_ba4 * 100
#Percentage of cells in dataset that co-express PAX3 + PDGFRA
#CB
PAX3_cells_cb <- length(which(FetchData(cb_opcs, vars = PAX3) > PAX3.cutoff &
FetchData(cb_opcs, vars = PDGFRA) < PDGFRA.cutoff))
PDGFRA_cells_cb <- length(which(FetchData(cb_opcs, vars = PDGFRA) > PDGFRA.cutoff&
FetchData(cb_opcs, vars = PAX3) < PAX3.cutoff))
PAX3_PDGFRA_olig2_cells_cb <- length(which(FetchData(cb_opcs, vars = PDGFRA) >
PDGFRA.cutoff & FetchData(cb_opcs, vars = PAX3) >
PAX3.cutoff))
all_cells_incluster_cb <- table(cb_opcs@active.ident)
PAX3_cb <- PAX3_cells_cb/all_cells_incluster_cb * 100 # Percentage of cells in dataset that express PAX3
PDGFRA_cb <- PDGFRA_cells_cb/all_cells_incluster_cb * 100 #Percentage of cells in dataset that express PDGFRA
double_cb <- PAX3_PDGFRA_olig2_cells_cb/all_cells_incluster_cb * 100 #Percentage of cells in dataset that co-express PAX3 + PDGFRA
#CSC
PAX3_cells_csc <- length(which(FetchData(csc_opcs, vars = PAX3) > PAX3.cutoff&
FetchData(csc_opcs, vars = PDGFRA) < PDGFRA.cutoff))
PDGFRA_cells_csc <- length(which(FetchData(csc_opcs, vars = PDGFRA) > PDGFRA.cutoff &
FetchData(csc_opcs, vars = PAX3) < PAX3.cutoff))
PAX3_PDGFRA_olig2_cells_csc <- length(which(FetchData(csc_opcs, vars = PDGFRA) >
PDGFRA.cutoff & FetchData(csc_opcs, vars = PAX3) >
PAX3.cutoff))
all_cells_incluster_csc <- table(csc_opcs@active.ident)
PAX3_csc <- PAX3_cells_csc/all_cells_incluster_csc * 100
# Percentage of cells in dataset that express PAX3
PDGFRA_csc <- PDGFRA_cells_csc/all_cells_incluster_csc * 100
#Percentage of cells in dataset that express PDGFRA
double_csc <- PAX3_PDGFRA_olig2_cells_csc/all_cells_incluster_csc * 100
#Percentage of cells in dataset that co-express PAX3 + PDGFRA
df_snrna_seq <- data.frame(Tissue = c(rep("BA4", 4),
rep("CB", 4),
rep("CSC", 4)),
gene_expr = rep(c("PAX3+",
"PDGFRA+",
"PAX3+PDGFRA+",
"Other OPCs"), 3),
percentage = c(as.numeric(PAX3_ba4),
as.numeric(PDGFRA_ba4),
as.numeric(double_ba4),
100 - (as.numeric(PAX3_ba4)+
as.numeric(PDGFRA_ba4)+
as.numeric(double_ba4)),
as.numeric(PAX3_cb),
as.numeric(PDGFRA_cb),
as.numeric(double_cb),
100 - (as.numeric(PAX3_cb)+
as.numeric(PDGFRA_cb)+
as.numeric(double_cb)),
as.numeric(PAX3_csc),
as.numeric(PDGFRA_csc),
as.numeric(double_csc),
100 - (as.numeric(PAX3_csc)+
as.numeric(PDGFRA_csc)+
as.numeric(double_csc))))
ggplot(df_snrna_seq, aes(x = Tissue, y=percentage, fill = gene_expr))+
geom_bar(stat="identity")+scale_fill_manual(values= mycoloursP[24:50])
subs_data <- subset(df_snrna_seq, df_snrna_seq$gene_expr != "Other OPCs")
ggplot(subs_data, aes(x = Tissue, y=percentage, fill = gene_expr))+
geom_bar(stat="identity")+scale_fill_manual(values= mycoloursP[24:50])
ggplot(subs_data, aes(x = Tissue, y=percentage, fill = gene_expr))+
geom_bar(stat="identity", position = "fill")+scale_fill_manual(values= mycoloursP[24:50])
```
```{r}
PAX3_data <- subs_data
PAX3_data$coexpr <- "PAX3 PDGFRA"
PAX3_data$marker <- ifelse(PAX3_data$gene_expr == "PAX3+", "Marker1+",
ifelse(PAX3_data$gene_expr == "PDGFRA+", "PDGFRA+",
"Double+"))
comb_data <- rbind(nell1_data, PAX3_data)
subs_dat_opc <- subset(comb_data, comb_data$marker != "Marker1+")
```
```{r}
ggplot(subs_dat_opc, aes(x = coexpr, y=percentage, fill = marker))+
geom_bar(stat="identity", position = "fill")+
scale_fill_manual(values= mycoloursP[27:50]) +
theme_minimal()+
theme(axis.text.x = element_text(angle = -90))
```
```{r}
ggplot(subs_data, aes(x = Tissue, y=percentage, fill = gene_expr))+
geom_bar(stat="identity", position = "fill")+scale_fill_manual(values= mycoloursP[24:50])
```
OPC validation data
Taken from environment (68_Validation_Nell1_PDGFRA.Rmd and
58_Validation_PDGFRA_PAX3)
```{r}
n_dat <- data.frame(donor_id = nell1_subs_long$donor_id,
tissue = nell1_subs_long$tissue,
sample_id = nell1_subs_long$sample_id,
keycol = nell1_subs_long$keycol,
valuecol= nell1_subs_long$valuecol,
staining = nell1_subs_long$staining)
n_dat$marker <- ifelse(n_dat$keycol == "PDGFRA_NELL1",
"Double+", "PDGFRA+")
p_dat <- data.frame(donor_id = pax3_subs_long$donor_id,
tissue = pax3_subs_long$tissue,
sample_id = pax3_subs_long$sample_id,
keycol = pax3_subs_long$keycol,
valuecol= pax3_subs_long$valuecol,
staining = pax3_subs_long$staining)
p_dat$marker <- ifelse(p_dat$keycol == "double_pos",
"Double+", "PDGFRA+")
nell_pax <- rbind(n_dat, p_dat)
ggplot(nell_pax, aes(x = staining ,
y = valuecol,
fill = marker)) +
geom_bar(position="fill", stat="identity")+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
scale_fill_manual(values= mycoloursP[16:30])+
theme_minimal()+
theme(axis.text.x = element_text(angle = -90))
```
```{r}
sessionInfo()
```