F5_AB Sub-clustering of CSF myeloid cell subsets in VS-PWH.

About the Data

library(Seurat)
library(ggplot2)
library(cowplot)
library(dplyr)
set.seed(123)
#load data
load("data/6.annotated.rda")
FinalFilter

Subset Myeloid cells, recluster, and normalize

Myeloid <- subset(FinalFilter, cell_types=="Myeloid")
DefaultAssay(Myeloid) <- "RNA"
Myeloid <- FindVariableFeatures(Myeloid)
Myeloid <- RunPCA(Myeloid)
Myeloid <- RunUMAP(Myeloid, reduction = "pca", dims=1:50)
Myeloid <- FindNeighbors(Myeloid, reduction = "pca", dims = 1:50)
Myeloid <- FindClusters(Myeloid, resolution = 0.5)
table(Idents(Myeloid))
Myeloid$seurat_clusters[Myeloid$seurat_clusters == "0"] <- "1"
Myeloid$seurat_clusters <- droplevels(Myeloid$seurat_clusters)
Idents(Myeloid) <- Myeloid$seurat_clusters
#Dimplot
DimPlot(Myeloid, reduction = "umap", cols = c("navy", "cornflowerblue","lightsteelblue1","blue"))
#ggsave("plots/4.myeloid/umap_blue.svg", width = 6, height = 5)
#save(Myeloid, file = "data/7.Myeloid.rda")

Cluster Abundance across samples

table(Myeloid$seurat_clusters, Myeloid$ID)

tmp <-table(Myeloid$seurat_clusters, Myeloid$ID)
round(prop.table(tmp, margin = 2)*100,1)
abundance <- as.data.frame(round(prop.table(tmp, margin = 2)*100,1))
colnames(abundance) <- c("cluster", "ID", "Freq")

ggplot(abundance, aes(fill=cluster, y=Freq, x=ID)) + 
  geom_bar(position="stack", stat="identity") + theme_cowplot() +
  scale_fill_manual(values = c("navy", "cornflowerblue","lightsteelblue1","blue"))
#ggsave("plots/4.myeloid/Myel_abundance_blue.svg", width = 6, height = 5)

sessionInfo()