ADT Normalization

1. load libraries

2. Load Seurat Object

#Load Seurat Object merged from cell lines and a control(PBMC) after filtration
SS_All_samples_Merged <- load("../6-ADT_Normalization/All_Samples_Merged_NormalizedADT-scaled.Robj")

All_samples_Merged

An object of class Seurat 
63193 features across 49193 samples within 6 assays 
Active assay: ADT (28 features, 0 variable features)
 3 layers present: counts, data, scale.data
 5 other assays present: RNA, SCT, prediction.score.celltype.l1, prediction.score.celltype.l2, prediction.score.celltype.l3
 4 dimensional reductions calculated: pca, umap, integrated_dr, ref.umap

3. Normalize ADT

rownames(All_samples_Merged[["ADT"]])

 [1] "CD274"  "CD30"   "CD40"   "CD3"    "CD45RA" "CD7"    "CCR4"   "CD4"    "CD25"   "CD45RO" "PD1"    "CD44"   "CD5"   
[14] "CXCR3"  "CCR6"   "CD62L"  "CCR7"   "CD95"   "TCRab"  "CXCR4"  "CD2"    "CD28"   "CD127"  "CD45"   "CD26"   "CCR10" 
[27] "CCR8"   "CD19"  

# # Perform normalization and scaling
# All_samples_Merged <- NormalizeData(All_samples_Merged, normalization.method = "CLR", margin = 2)

4. Visualize multiple modalities side-by-side

# Now, we will visualize CD14 levels for RNA and protein By setting the default assay, we can
# visualize one or the other
DefaultAssay(All_samples_Merged) <- "ADT"
p1 <- FeaturePlot(All_samples_Merged, "CD19", cols = c("lightgrey", "darkgreen")) + ggtitle("CD19 protein")
DefaultAssay(All_samples_Merged) <- "SCT"
p2 <- FeaturePlot(All_samples_Merged, "CD19") + ggtitle("CD19 RNA")

# place plots side-by-side
p1 | p2

Key(All_samples_Merged[["RNA"]])

[1] "rna_"

Key(All_samples_Merged[["SCT"]])

[1] "sct_"

Key(All_samples_Merged[["ADT"]])

[1] "adt_"

# Now, we can include the key in the feature name, which overrides the default assay
p1 <- FeaturePlot(All_samples_Merged, "adt_CD19", cols = c("lightgrey", "darkgreen")) + ggtitle("CD19 protein")
p2 <- FeaturePlot(All_samples_Merged, "rna_CD19") + ggtitle("CD19 RNA")
p3 <- FeaturePlot(All_samples_Merged, "sct_CD19") + ggtitle("CD19 RNA_SCT")
p1 | p2 | p3

# Now, we can include the key in the feature name, which overrides the default assay
p1 <- FeaturePlot(All_samples_Merged, "adt_CD274", cols = c("lightgrey", "darkgreen")) + ggtitle("CD274 protein")
p2 <- FeaturePlot(All_samples_Merged, "rna_CD274") + ggtitle("CD274 RNA")
p3 <- FeaturePlot(All_samples_Merged, "sct_CD274") + ggtitle("CD274 RNA_SCT")
p1 | p2 | p3

# Now, we can include the key in the feature name, which overrides the default assay
p1 <- FeaturePlot(All_samples_Merged, "adt_CD7", cols = c("lightgrey", "darkgreen")) + ggtitle("CD7 protein")
p2 <- FeaturePlot(All_samples_Merged, "rna_CD7") + ggtitle("CD7 RNA")
p3 <- FeaturePlot(All_samples_Merged, "sct_CD7") + ggtitle("CD7 RNA_SCT")
p1 | p2 | p3

adt_markers <- FindMarkers(All_samples_Merged, ident.1 = 8, assay = "ADT")
rna_markers <- FindMarkers(All_samples_Merged, ident.1 = 8, assay = "RNA")
SCT_markers <- FindMarkers(All_samples_Merged, ident.1 = 8, assay = "SCT")

head(adt_markers)

head(rna_markers)

head(SCT_markers)

DefaultAssay -> "SCT"
Idents(object=All_samples_Merged) <- "cell_line"
FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD2")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD3")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD5")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD28")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD127")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD45")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD19")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD7")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD25")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD26")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD45RA")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD45RO")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD62L")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CCR7")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CCR4")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CCR6")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CCR8")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CCR10")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CXCR3")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CXCR4")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD95")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD30")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD40")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD44")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD45")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_CD274")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "adt_PD1")

FeatureScatter(All_samples_Merged, feature1 = "adt_CD4", feature2 = "TCRab")

Warning: Could not find TCRab in the default search locations, found in ‘ADT’ assay instead