spRandom-seq/01_Preprocessing_10X_data.R at main · WangycLab/spRandom-seq · GitHub

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source("./Helper_functions.R")


######### Process 10X mouse brain data #########
visiumv1_coord <- read.table("./Data/visium-v1_coordinates.txt")
colnames(visiumv1_coord) <- c("Barcode", "X", "Y")
visiumv1_coord <- visiumv1_coord %>%
  arrange(X,Y)
dataObj_10X_Visium <- readRDS("./10X_Data/10X_Visium_Mouse_Brain_v2_res.rds")

dataObj_10X_Visium_temp <- CreateSeuratObject(
  counts = Read10X("./Data/10X_Mouse_Brain_raw/"),
  min.cells = 1
)

dataObj_10X_Visium_temp <- subset(dataObj_10X_Visium_temp, cells = dataObj_10X_Visium@meta.data %>%
                                    rownames_to_column(var = "Barcode") %>%
                                    mutate(Barcode = gsub("-1", "", Barcode)) %>%
                                    pull(Barcode))
dataObj_10X_Visium_temp[['RNA']] <- as(object = dataObj_10X_Visium_temp[['RNA']], Class = "Assay")

dataObj_10X_Visium_temp@meta.data <- dataObj_10X_Visium_temp@meta.data %>%
  rownames_to_column(var = "Barcode") %>%
  mutate(Barcode = gsub("-1", "", Barcode)) %>%
  inner_join(., visiumv1_coord, by = "Barcode") %>%
  column_to_rownames(var = "Barcode")

ggplot(data = dataObj_10X_Visium_temp@meta.data,
       mapping = aes(x = X, y = Y, color = nFeature_RNA)) +
  geom_point(size = 2.5) +
  #scale_color_manual(values = cbp2) +
  coord_flip() +
  xlim(0,max(dataObj_10X_Visium_temp@meta.data$X)+2) +
  ylim(0,max(dataObj_10X_Visium_temp@meta.data$Y)+2) +
  theme_bw()

dataObj_10X_Visium_temp <- CreateSeuratObject(counts = dataObj_10X_Visium_temp@assays$RNA@counts) %>%
  SCTransform(., ncells = 3000, verbose = FALSE) %>%
  RunPCA(verbose = FALSE) %>%
  RunUMAP(dims = 1:30) %>%
  FindNeighbors(dims = 1:30, verbose = FALSE) %>%
  FindClusters(verbose = FALSE)

dataObj_10X_Visium_temp@meta.data <- dataObj_10X_Visium_temp@meta.data %>%
  rownames_to_column(var = "Barcode") %>%
  mutate(Barcode = gsub("-1", "", Barcode)) %>%
  inner_join(., visiumv1_coord, by = "Barcode") %>%
  column_to_rownames(var = "Barcode")

ggplot(data = dataObj_10X_Visium_temp@meta.data,
       mapping = aes(x = X, y = Y, color = seurat_clusters)) +
  geom_point(size = 2.5) +
  scale_color_manual(values = cbp2) +
  #coord_flip() +
  xlim(0,max(dataObj_10X_Visium_temp@meta.data$X)+2) +
  ylim(0,max(dataObj_10X_Visium_temp@meta.data$Y)+2) +
  theme_bw()

median(dataObj_10X_Visium_temp$nCount_RNA)
median(dataObj_10X_Visium_temp$nFeature_RNA)

saveRDS(dataObj_10X_Visium_temp, "./Data/10X_mmBrain.rds")