Differential Expression Analysis of 1 vs 2 in L3-L4
Nasir Mahmood Abbasi
2024-11-13
1. load libraries
2. Load Seurat Object
load("/home/bioinfo/0-imp_Robj/Harmony_integrated_All_samples_Merged_with_PBMC10x_with_harmony_clustering.Robj")
3. Initial Visualization
All_samples_Merged <- SetIdent(All_samples_Merged, value = "Harmony_snn_res.0.9")
DimPlot(All_samples_Merged,group.by = "cell_line",
reduction = "umap.harmony",
label.size = 3,
repel = T,
label = T)
DimPlot(All_samples_Merged,
group.by = "Harmony_snn_res.0.9",
reduction = "umap.harmony",
label.size = 3,
repel = T,
label = T)
DimPlot(All_samples_Merged, group.by = "predicted.celltype.l2",
reduction = "umap.harmony",
label.size = 3,
repel = T,
label = T)
table(All_samples_Merged$predicted.celltype.l2, All_samples_Merged$SCT_snn_res.0.9)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
ASDC 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0
B intermediate 0 0 0 0 0 1 0 0 0 0 0 3 664 0 1 17 0 4 0 2 2 0
B memory 1 5 1 0 0 2 218 7 0 0 0 3 260 1 0 2 1 5 0 13 1 0
B naive 0 0 0 0 0 1 0 0 0 0 0 7 1170 0 1 0 0 6 0 0 1 6
CD14 Mono 0 1 2 0 0 1 38 0 9 0 20 2522 0 1 0 812 0 218 6 0 0 183
CD16 Mono 0 1 0 0 0 0 0 0 0 0 0 105 0 0 0 19 0 0 0 0 0 1
CD4 CTL 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 1
CD4 Naive 1953 0 0 0 0 35 0 0 0 0 0 0 7 0 0 0 0 6 0 0 40 1
CD4 Proliferating 1 4409 4338 1901 3476 6 1977 2989 2946 3183 402 1 2 1846 1 0 825 28 48 498 133 0
CD4 TCM 2606 805 19 8 69 3290 1458 52 331 15 2643 18 65 107 53 32 1 392 580 44 256 20
CD4 TEM 6 0 0 0 0 69 0 0 0 0 1 0 0 0 15 0 0 3 0 0 0 0
CD8 Naive 1315 0 0 0 0 15 0 0 0 0 0 0 2 0 1 1 0 18 1 0 17 2
CD8 Proliferating 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
CD8 TCM 121 1 0 0 0 237 0 0 9 0 0 0 2 0 92 0 0 6 7 0 1 0
CD8 TEM 5 0 0 1 0 40 7 0 5 0 0 1 1 0 324 0 0 0 0 0 7 0
cDC1 0 0 0 0 0 0 5 0 0 0 0 13 0 0 0 0 0 0 0 2 1 0
cDC2 0 0 0 0 1 0 47 0 1 0 0 122 0 0 0 0 0 0 0 3 0 2
dnT 7 0 0 0 0 24 7 0 0 0 1 0 2 0 0 3 0 17 0 0 20 0
gdT 9 0 0 0 0 6 0 0 0 0 0 0 0 0 77 0 0 0 0 0 1 0
HSPC 0 1 54 0 705 0 37 757 0 197 3 6 1 0 1 0 1 3 6 39 7 0
ILC 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 0 1 0 0 1 0
MAIT 0 0 0 0 0 8 0 0 0 0 0 0 0 0 228 0 0 1 0 0 3 2
NK 0 0 0 0 0 0 0 0 0 0 0 0 1 0 518 1 0 1 0 0 7 6
NK Proliferating 0 0 9 2374 5 0 8 6 443 218 0 0 0 15 2 0 38 5 0 11 32 0
NK_CD56bright 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 2 0
pDC 0 0 0 0 0 0 0 0 0 0 0 56 0 0 0 0 0 0 0 0 0 0
Plasmablast 0 0 0 0 0 0 0 0 0 0 0 5 11 0 0 0 0 2 0 0 1 0
Platelet 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0
Treg 90 0 0 0 0 166 9 0 1 0 0 0 5 0 0 0 0 41 0 0 39 1
22 23 24
ASDC 0 0 0
B intermediate 2 0 0
B memory 2 1 0
B naive 0 0 0
CD14 Mono 7 3 0
CD16 Mono 0 0 0
CD4 CTL 0 0 0
CD4 Naive 0 0 1
CD4 Proliferating 1 0 0
CD4 TCM 3 0 11
CD4 TEM 0 0 0
CD8 Naive 0 1 0
CD8 Proliferating 0 0 0
CD8 TCM 0 0 1
CD8 TEM 0 0 0
cDC1 21 0 0
cDC2 53 0 0
dnT 0 0 1
gdT 0 0 0
HSPC 4 7 5
ILC 0 0 0
MAIT 0 0 0
NK 0 0 0
NK Proliferating 0 1 0
NK_CD56bright 0 0 0
pDC 0 0 0
Plasmablast 0 0 0
Platelet 0 30 0
Treg 1 0 04. Perform DE analysis
# Find markers using the FindMarkers between 1vs2 and 6vs16
All_samples_Merged <- SetIdent(All_samples_Merged, value = "SCT_snn_res.0.9")
C1_vs_C2 <- FindMarkers(All_samples_Merged,
ident.1 = 1,
ident.2 = 2
)Perform DE analysis
# Find markers using the FindMarkers between 1vs2 and 6vs16
All_samples_Merged <- SetIdent(All_samples_Merged, value = "SCT_snn_res.0.9")
C6_vs_C16 <- FindMarkers(All_samples_Merged,
ident.1 = 6,
ident.2 = 16
)
# Convert to data frame and add gene names as a new column
C6_vs_C16 <- as.data.frame(C6_vs_C16)
C6_vs_C16$gene <- rownames(C6_vs_C16)
# Rearranging the columns for better readability (optional)
C6_vs_C16 <- C6_vs_C16[, c("gene", "p_val", "avg_log2FC", "pct.1", "pct.2", "p_val_adj")]
write.csv(C6_vs_C16, "C6_vs_C16", row.names = FALSE)
- Volcano Plot-C1vsC2
EnhancedVolcano(C1_vs_C2 ,
lab=rownames(C1_vs_C2),
x ="avg_log2FC",
y ="p_val_adj",
title = "C1_vs_C2",
pCutoff = 0.05,
FCcutoff = 1,
legendPosition = 'right',
labCol = 'black',
labFace = 'bold',
boxedLabels = TRUE,
pointSize = 3.0,
labSize = 5.0,
drawConnectors = TRUE,
widthConnectors = 0.25)Warning: One or more p-values is 0. Converting to 10^-1 * current lowest non-zero p-value...
# EnhancedVolcano(Patient_cell_lines_vs_PBMC_Tcells ,
# lab=rownames(Patient_cell_lines_vs_PBMC_Tcells),
# x ="avg_log2FC",
# y ="p_val_adj",
# selectLab = c('EPCAM','BCAT1','KIR3DL2',
# 'FOXM1','TWIST1','TNFSF9','CD80','CD7','IL1B', 'TRBV7.6','TRBV5.4','TRBV12.4'),
# title = "Sézary Cell Lines vs PBMC T cells",
# xlab = bquote(~Log[2]~ 'fold change'),
# pCutoff = 0.05,
# FCcutoff = 1,
# legendPosition = 'right',
# legendLabSize = 14,
# legendIconSize = 4.0,
# labCol = 'black',
# labFace = 'bold',
# boxedLabels = TRUE,
# pointSize = 3.0,
# labSize = 5.0,
# drawConnectors = TRUE,
# widthConnectors = 0.75,
# colConnectors = 'black')
EnhancedVolcano(C1_vs_C2,
lab = ifelse(C1_vs_C2$avg_log2FC > 1 & C1_vs_C2$p_val_adj < 0.05,
rownames(C1_vs_C2),
""), # Label only significant genes
x = "avg_log2FC",
y = "p_val_adj",
title = "C1_vs_C2",
pCutoff = 0.05,
FCcutoff = 1,
legendPosition = 'right',
labCol = 'black',
labFace = 'bold',
boxedLabels = TRUE,
pointSize = 3.0,
labSize = 5.0,
drawConnectors = TRUE,
widthConnectors = 0.25)Warning: One or more p-values is 0. Converting to 10^-1 * current lowest non-zero p-value...
EnhancedVolcano(C1_vs_C2,
lab = ifelse((C1_vs_C2$avg_log2FC > 1.5 | C1_vs_C2$avg_log2FC < -1.5) &
C1_vs_C2$p_val_adj < 0.05,
rownames(C1_vs_C2),
""), # Label only significant genes
x = "avg_log2FC",
y = "p_val_adj",
title = "C1_vs_C2",
pCutoff = 0.05,
FCcutoff = 1,
legendPosition = 'right',
labCol = 'black',
labFace = 'bold',
boxedLabels = TRUE,
pointSize = 3.0,
labSize = 5.0,
drawConnectors = TRUE,
widthConnectors = 0.25)Warning: One or more p-values is 0. Converting to 10^-1 * current lowest non-zero p-value...
# All_samples_Merged <- SetIdent(All_samples_Merged, value = "SCT_snn_res.0.9")
#
# L2_Thesholds <- FindMarkers(All_samples_Merged, ident.1 = "4", ident.2 = "9", min.pct = 0.10, thresh.use = 0.25)
#
# EnhancedVolcano(L2_Thesholds ,
# lab=rownames(L2_Thesholds),
# x ="avg_log2FC",
# y ="p_val_adj",
# title = "4_vs_9",
# pCutoff = 0.05,
# FCcutoff = 1,
# legendPosition = 'right',
# labCol = 'black',
# labFace = 'bold',
# boxedLabels = TRUE,
# pointSize = 3.0,
# labSize = 3.0,
# drawConnectors = FALSE,
# widthConnectors = 0.75)
C6vsC16
EnhancedVolcano(C6_vs_C16 ,
lab=rownames(C6_vs_C16),
x ="avg_log2FC",
y ="p_val_adj",
title = "C6_vs_C16",
pCutoff = 0.05,
FCcutoff = 1,
legendPosition = 'right',
labCol = 'black',
labFace = 'bold',
boxedLabels = TRUE,
pointSize = 3.0,
labSize = 5.0,
drawConnectors = TRUE,
widthConnectors = 0.25)Warning: One or more p-values is 0. Converting to 10^-1 * current lowest non-zero p-value...
# EnhancedVolcano(Patient_cell_lines_vs_PBMC_Tcells ,
# lab=rownames(Patient_cell_lines_vs_PBMC_Tcells),
# x ="avg_log2FC",
# y ="p_val_adj",
# selectLab = c('EPCAM','BCAT1','KIR3DL2',
# 'FOXM1','TWIST1','TNFSF9','CD80','CD7','IL1B', 'TRBV7.6','TRBV5.4','TRBV12.4'),
# title = "Sézary Cell Lines vs PBMC T cells",
# xlab = bquote(~Log[2]~ 'fold change'),
# pCutoff = 0.05,
# FCcutoff = 1,
# legendPosition = 'right',
# legendLabSize = 14,
# legendIconSize = 4.0,
# labCol = 'black',
# labFace = 'bold',
# boxedLabels = TRUE,
# pointSize = 3.0,
# labSize = 5.0,
# drawConnectors = TRUE,
# widthConnectors = 0.75,
# colConnectors = 'black')
EnhancedVolcano(C6_vs_C16,
lab = ifelse(C6_vs_C16$avg_log2FC > 1 & C6_vs_C16$p_val_adj < 0.05,
rownames(C6_vs_C16),
""), # Label only significant genes
x = "avg_log2FC",
y = "p_val_adj",
title = "C6_vs_C16",
pCutoff = 0.05,
FCcutoff = 1,
legendPosition = 'right',
labCol = 'black',
labFace = 'bold',
boxedLabels = TRUE,
pointSize = 3.0,
labSize = 5.0,
drawConnectors = TRUE,
widthConnectors = 0.25)Warning: One or more p-values is 0. Converting to 10^-1 * current lowest non-zero p-value...
EnhancedVolcano(C6_vs_C16,
lab = ifelse((C6_vs_C16$avg_log2FC > 1.5 | C6_vs_C16$avg_log2FC < -1.5) &
C6_vs_C16$p_val_adj < 0.05,
rownames(C6_vs_C16),
""), # Label only significant genes
x = "avg_log2FC",
y = "p_val_adj",
title = "C6_vs_C16",
pCutoff = 0.05,
FCcutoff = 1,
legendPosition = 'right',
labCol = 'black',
labFace = 'bold',
boxedLabels = TRUE,
pointSize = 3.0,
labSize = 5.0,
drawConnectors = TRUE,
widthConnectors = 0.25)Warning: One or more p-values is 0. Converting to 10^-1 * current lowest non-zero p-value...
# All_samples_Merged <- SetIdent(All_samples_Merged, value = "SCT_snn_res.0.9")
#
# L2_Thesholds <- FindMarkers(All_samples_Merged, ident.1 = "4", ident.2 = "9", min.pct = 0.10, thresh.use = 0.25)
#
# EnhancedVolcano(L2_Thesholds ,
# lab=rownames(L2_Thesholds),
# x ="avg_log2FC",
# y ="p_val_adj",
# title = "4_vs_9",
# pCutoff = 0.05,
# FCcutoff = 1,
# legendPosition = 'right',
# labCol = 'black',
# labFace = 'bold',
# boxedLabels = TRUE,
# pointSize = 3.0,
# labSize = 3.0,
# drawConnectors = FALSE,
# widthConnectors = 0.75)
---
title: "Differential Expression Analysis of 1 vs 2 in L3-L4"
author: Nasir Mahmood Abbasi
date: "`r Sys.Date()`"
output:
  #rmdformats::readthedown
  html_notebook:
    toc: true
    toc_float: true
    toc_collapsed: true
---

# 1. load libraries
```{r setup, include=FALSE}
library(Seurat)
library(SeuratObject)
library(SeuratData)
library(patchwork)
library(harmony)
library(ggplot2)
library(cowplot)
library(reticulate)
library(Azimuth)
library(dplyr)
library(Rtsne)
library(harmony)
library(gridExtra)
library(EnhancedVolcano)
```

# 2. Load Seurat Object 
```{r load_seurat, fig.height=6, fig.width=10}

 load("/home/bioinfo/0-imp_Robj/Harmony_integrated_All_samples_Merged_with_PBMC10x_with_harmony_clustering.Robj")
 

```

# 3. Initial Visualization
```{r data1, fig.height=8, fig.width=12}
All_samples_Merged <- SetIdent(All_samples_Merged, value = "Harmony_snn_res.0.9")
  


DimPlot(All_samples_Merged,group.by = "cell_line", 
        reduction = "umap.harmony",
        label.size = 3,
        repel = T,
        label = T)

DimPlot(All_samples_Merged,
        group.by = "Harmony_snn_res.0.9", 
        reduction = "umap.harmony",
        label.size = 3,
        repel = T,
        label = T)


DimPlot(All_samples_Merged, group.by = "predicted.celltype.l2", 
        reduction = "umap.harmony",
        label.size = 3,
        repel = T,
        label = T)

 
table(All_samples_Merged$predicted.celltype.l2, All_samples_Merged$SCT_snn_res.0.9)

```

# 4. Perform DE analysis 
```{r data2, fig.height=8, fig.width=12}

# Find markers using the FindMarkers between 1vs2 and 6vs16 


All_samples_Merged <- SetIdent(All_samples_Merged, value = "SCT_snn_res.0.9")

C1_vs_C2 <- FindMarkers(All_samples_Merged, 
                           ident.1 = 1,
                           ident.2 = 2
                           )


# Convert to data frame and add gene names as a new column
 C1_vs_C2 <- as.data.frame(C1_vs_C2)
C1_vs_C2$gene <- rownames(C1_vs_C2)

# Rearranging the columns for better readability (optional)
C1_vs_C2 <- C1_vs_C2[, c("gene", "p_val", "avg_log2FC", "pct.1", "pct.2", "p_val_adj")]

write.csv(C1_vs_C2, "C1_vs_C2", row.names = FALSE)


```

##  Perform DE analysis 
```{r data3, fig.height=8, fig.width=12}

# Find markers using the FindMarkers between 1vs2 and 6vs16 


All_samples_Merged <- SetIdent(All_samples_Merged, value = "SCT_snn_res.0.9")

C6_vs_C16 <- FindMarkers(All_samples_Merged, 
                           ident.1 = 6,
                           ident.2 = 16
                           )


# Convert to data frame and add gene names as a new column
 C6_vs_C16 <- as.data.frame(C6_vs_C16)
C6_vs_C16$gene <- rownames(C6_vs_C16)

# Rearranging the columns for better readability (optional)
C6_vs_C16 <- C6_vs_C16[, c("gene", "p_val", "avg_log2FC", "pct.1", "pct.2", "p_val_adj")]

write.csv(C6_vs_C16, "C6_vs_C16", row.names = FALSE)


```

5. Volcano Plot-C1vsC2
```{r enhancedV, fig.height=8, fig.width=12}

EnhancedVolcano(C1_vs_C2 , 
                lab=rownames(C1_vs_C2),
                x ="avg_log2FC", 
                y ="p_val_adj",
                title = "C1_vs_C2",
                pCutoff = 0.05,
                FCcutoff = 1, 
                legendPosition = 'right', 
                labCol = 'black',
                labFace = 'bold',
                boxedLabels = TRUE,
                pointSize = 3.0,
                labSize = 5.0, 
                drawConnectors = TRUE,
                widthConnectors = 0.25)

# EnhancedVolcano(Patient_cell_lines_vs_PBMC_Tcells , 
#                 lab=rownames(Patient_cell_lines_vs_PBMC_Tcells),
#                 x ="avg_log2FC", 
#                 y ="p_val_adj",
#                 selectLab = c('EPCAM','BCAT1','KIR3DL2',
#       'FOXM1','TWIST1','TNFSF9','CD80','CD7','IL1B', 'TRBV7.6','TRBV5.4','TRBV12.4'),
#                 title = "Sézary Cell Lines vs PBMC T cells",
#                  xlab = bquote(~Log[2]~ 'fold change'),
#                 pCutoff = 0.05,
#                 FCcutoff = 1, 
#                 legendPosition = 'right', 
#                 legendLabSize = 14,
#                 legendIconSize = 4.0,
#                 labCol = 'black',
#                 labFace = 'bold',
#                 boxedLabels = TRUE,
#                 pointSize = 3.0,
#                 labSize = 5.0, 
#                 drawConnectors = TRUE,
#                 widthConnectors = 0.75,
#                 colConnectors = 'black')


EnhancedVolcano(C1_vs_C2, 
                lab = ifelse(C1_vs_C2$avg_log2FC > 1 & C1_vs_C2$p_val_adj < 0.05, 
                             rownames(C1_vs_C2), 
                             ""),  # Label only significant genes
                x = "avg_log2FC", 
                y = "p_val_adj",
                title = "C1_vs_C2",
                pCutoff = 0.05,
                FCcutoff = 1, 
                legendPosition = 'right', 
                labCol = 'black',
                labFace = 'bold',
                boxedLabels = TRUE,
                pointSize = 3.0,
                labSize = 5.0, 
                drawConnectors = TRUE,
                widthConnectors = 0.25)

EnhancedVolcano(C1_vs_C2, 
                lab = ifelse((C1_vs_C2$avg_log2FC > 1.5 | C1_vs_C2$avg_log2FC < -1.5) & 
                             C1_vs_C2$p_val_adj < 0.05, 
                             rownames(C1_vs_C2), 
                             ""),  # Label only significant genes
                x = "avg_log2FC", 
                y = "p_val_adj",
                title = "C1_vs_C2",
                pCutoff = 0.05,
                FCcutoff = 1, 
                legendPosition = 'right', 
                labCol = 'black',
                labFace = 'bold',
                boxedLabels = TRUE,
                pointSize = 3.0,
                labSize = 5.0, 
                drawConnectors = TRUE,
                widthConnectors = 0.25)


# All_samples_Merged <- SetIdent(All_samples_Merged, value = "SCT_snn_res.0.9")
# 
# L2_Thesholds <- FindMarkers(All_samples_Merged, ident.1 = "4", ident.2 = "9", min.pct = 0.10, thresh.use = 0.25)
# 
# EnhancedVolcano(L2_Thesholds , 
#                 lab=rownames(L2_Thesholds),
#                 x ="avg_log2FC", 
#                 y ="p_val_adj",
#                 title = "4_vs_9",
#                 pCutoff = 0.05,
#                 FCcutoff = 1, 
#                 legendPosition = 'right', 
#                 labCol = 'black',
#                 labFace = 'bold',
#                 boxedLabels = TRUE,
#                 pointSize = 3.0,
#                 labSize = 3.0, 
#                 drawConnectors = FALSE,
#                 widthConnectors = 0.75)



```


## C6vsC16
```{r enhancedV2, fig.height=8, fig.width=12}

EnhancedVolcano(C6_vs_C16 , 
                lab=rownames(C6_vs_C16),
                x ="avg_log2FC", 
                y ="p_val_adj",
                title = "C6_vs_C16",
                pCutoff = 0.05,
                FCcutoff = 1, 
                legendPosition = 'right', 
                labCol = 'black',
                labFace = 'bold',
                boxedLabels = TRUE,
                pointSize = 3.0,
                labSize = 5.0, 
                drawConnectors = TRUE,
                widthConnectors = 0.25)

# EnhancedVolcano(Patient_cell_lines_vs_PBMC_Tcells , 
#                 lab=rownames(Patient_cell_lines_vs_PBMC_Tcells),
#                 x ="avg_log2FC", 
#                 y ="p_val_adj",
#                 selectLab = c('EPCAM','BCAT1','KIR3DL2',
#       'FOXM1','TWIST1','TNFSF9','CD80','CD7','IL1B', 'TRBV7.6','TRBV5.4','TRBV12.4'),
#                 title = "Sézary Cell Lines vs PBMC T cells",
#                  xlab = bquote(~Log[2]~ 'fold change'),
#                 pCutoff = 0.05,
#                 FCcutoff = 1, 
#                 legendPosition = 'right', 
#                 legendLabSize = 14,
#                 legendIconSize = 4.0,
#                 labCol = 'black',
#                 labFace = 'bold',
#                 boxedLabels = TRUE,
#                 pointSize = 3.0,
#                 labSize = 5.0, 
#                 drawConnectors = TRUE,
#                 widthConnectors = 0.75,
#                 colConnectors = 'black')


EnhancedVolcano(C6_vs_C16, 
                lab = ifelse(C6_vs_C16$avg_log2FC > 1 & C6_vs_C16$p_val_adj < 0.05, 
                             rownames(C6_vs_C16), 
                             ""),  # Label only significant genes
                x = "avg_log2FC", 
                y = "p_val_adj",
                title = "C6_vs_C16",
                pCutoff = 0.05,
                FCcutoff = 1, 
                legendPosition = 'right', 
                labCol = 'black',
                labFace = 'bold',
                boxedLabels = TRUE,
                pointSize = 3.0,
                labSize = 5.0, 
                drawConnectors = TRUE,
                widthConnectors = 0.25)

EnhancedVolcano(C6_vs_C16, 
                lab = ifelse((C6_vs_C16$avg_log2FC > 1.5 | C6_vs_C16$avg_log2FC < -1.5) & 
                             C6_vs_C16$p_val_adj < 0.05, 
                             rownames(C6_vs_C16), 
                             ""),  # Label only significant genes
                x = "avg_log2FC", 
                y = "p_val_adj",
                title = "C6_vs_C16",
                pCutoff = 0.05,
                FCcutoff = 1, 
                legendPosition = 'right', 
                labCol = 'black',
                labFace = 'bold',
                boxedLabels = TRUE,
                pointSize = 3.0,
                labSize = 5.0, 
                drawConnectors = TRUE,
                widthConnectors = 0.25)


# All_samples_Merged <- SetIdent(All_samples_Merged, value = "SCT_snn_res.0.9")
# 
# L2_Thesholds <- FindMarkers(All_samples_Merged, ident.1 = "4", ident.2 = "9", min.pct = 0.10, thresh.use = 0.25)
# 
# EnhancedVolcano(L2_Thesholds , 
#                 lab=rownames(L2_Thesholds),
#                 x ="avg_log2FC", 
#                 y ="p_val_adj",
#                 title = "4_vs_9",
#                 pCutoff = 0.05,
#                 FCcutoff = 1, 
#                 legendPosition = 'right', 
#                 labCol = 'black',
#                 labFace = 'bold',
#                 boxedLabels = TRUE,
#                 pointSize = 3.0,
#                 labSize = 3.0, 
#                 drawConnectors = FALSE,
#                 widthConnectors = 0.75)



```

