scRNAseq Fibroblast Subpopulation Analysis

Author

Ahmed M. Elhossiny

This section focuses on a detailed sub-analysis of the fibroblast population. We subset the fibroblast cells from the main dataset, reclustered them to identify distinct fibroblast subtypes.

1 Setup and Environment Configuration

Code

suppressPackageStartupMessages({
  library(Seurat)
  library(SeuratWrappers)
  library(tidyverse)
  library(scCustomize)
  library(CellChat)
  library(slurmR)
  library(tidyverse)
  library(reticulate)
  library(qs)
  library(clustree)
  library(org.Hs.eg.db)
  library(CoGAPS)
  library(Seurat)
  library(slurmR)
  library(cowplot)
  library(tidyverse)
  library(pheatmap)
  library(qs)
})

ref <- qread("../outputs/scRNAseq_Analysis/scRef.qs")

2 Subset and Re-cluster Fibroblasts

Code

fibro <- subset(ref, subset = main_annotation_scvi == 'Fibroblasts')
samples_keep <- names(table(fibro$sample_id))[table(fibro$sample_id) > 10]
fibro$sample_id <- factor(as.character(fibro$sample_id))
fibro <- subset(fibro, subset = sample_id %in% samples_keep)
fibro <- RunUMAP(fibro, reduction = 'integrated.scvi', dims = 1:30)
fibro <- FindNeighbors(fibro, reduction = 'integrated.scvi', dims = 1:30)
res <- seq(from = 0.05, to = 1, by = 0.05)
for (x in res) {
  fibro <- FindClusters(fibro, resolution = x, cluster.name = paste0("res.", x))
}
clustree(fibro, prefix = 'res.', layout = "sugiyama")
fibro <- FindClusters(fibro, resolution = 0.2)
fibro <- JoinLayers(fibro)

3 Annotate Fibroblast Subtypes

Code

markers <- FindAllMarkers(fibro)
markers$scores <- markers$avg_log2FC * markers$pct.1
fibro <- subset(fibro, subset = seurat_clusters %in% c(0, 2, 3, 4, 5, 6, 7))
fibro <- RunUMAP(fibro, reduction = 'integrated.scvi', dims = 1:30)
new_idents <- c(
  '0' = 'IGF1+_Fibro',
  '2' = 'SFRP4+_Fibro',
  '3' = 'LRRC15+_Fibro',
  '4' = 'RORA+_Fibro',
  '5' = 'HAS1+_Fibro',
  '6' = 'COL1A1+_Fibro',
  '7' = 'CD74+_Fibro'
)
fibro <- RenameIdents(fibro, new_idents)
fibro$fibro_subtypes <- Idents(fibro)
fibro$fibro_subtypes <- factor(
  fibro$fibro_subtypes,
  levels = c(
    'IGF1+_Fibro',
    'HAS1+_Fibro',
    'COL1A1+_Fibro',
    'LRRC15+_Fibro',
    'SFRP4+_Fibro',
    'RORA+_Fibro',
    'CD74+_Fibro'
  )
)
qsave(fibro, "../outputs/scRNAseq_Analysis/scRef_fibro.qs")

Code

ref <- qread("../outputs/scRNAseq_Analysis/scRef_fibro.qs")

Code

cols <- scPalette(length(unique(fibro$fibro_subtypes)))
names(cols) <- levels(fibro$fibro_subtypes)
DimPlot(fibro, group.by = 'fibro_subtypes', cols = cols) +
  ggtitle("scRNAseq Fibroblasts Subtypes")

markers <- FindAllMarkers(fibro, group.by = 'fibro_subtypes')
markers$scores <- markers$avg_log2FC * markers$pct.1
top_markers <- markers %>%
  group_by(cluster) %>%
  top_n(n = 30, wt = scores) %>%
  dplyr::select(cluster, gene) %>%
  split(.$cluster) %>%
  lapply(pull, gene)

Code

sessionInfo()