CSF Bulk 2. Differential Expression CSF vs PBMC

About the Data

DESeq2 analysis of CSF and PBMC myeloid and lymphoid cells with design = ~ 0 + group the groups include: PBMC_Myel, PBMC_Lym, CSF_Myel, CSF_Lym. Differential expression between CSF and PBMC in either myeloid cells or lymphoid cells. n = 6 CSF samples and 6 PBMC samples each bulk sorted for myeloid and lymphoid cells.

library(DESeq2)
library(ggplot2)
library(cowplot)
library(pheatmap)
library(ggrepel)
library(grid)
library(rstatix)

Load Data

load("data/filt_dds_env.rda")
resultsNames(dds)

GOIs

# plot genes of interest
GOIs <- c("ID1", "A2M", "GNLY", "PROKR2")

for (p in GOIs){
  geneid <- rownames(dds)[which(mcols(dds)$gene_name == p)]
  d <- plotCounts(dds, gene=geneid, intgroup=c("tissue", "cell"), returnData = TRUE)

  plot <- ggplot(d, aes(x=cell, y=count, color=tissue)) + 
    geom_point(size=3, position=position_jitterdodge(dodge.width = 0.5, jitter.width = 0)) + 
    stat_summary(fun.y = "mean", geom = "point", aes(group = tissue), 
                 position = position_dodge(width = 0.5), color = "black", shape = "_", size = 10) + 
    scale_color_manual(values = c("cornflowerblue","red")) + 
    expand_limits(y=0) + ylab("normalized count") + xlab("") + labs(subtitle = p) + 
    theme_cowplot() + theme(legend.position = "none")
  print(plot)
  # CSF = blue, PBMC = red
  # save plot
  #350x350
  ggsave(filename=paste(p,".jpeg", sep = ""), plot = plot, width = 60, height = 80, units = "mm", path = "plots/", bg="white")
}

sessionInfo()