GSE263678

Cisplatin treated mice

## 
## TRUE 
##   32

PCA plot

Male samples are straying to the left of plot, high variance in Day 0 samples (unclear if Day 0 samples received cisplatin based on metadata).

Will not be including male samples going forward

PCA <- prcomp(t(v$E), scale = FALSE)

percentVar <- round(100*PCA$sdev^2/sum(PCA$sdev^2),1)
sd_ratio <- sqrt(percentVar[2] / percentVar[1])

dataGG <- data.frame(PC1 = PCA$x[,1], PC2 = PCA$x[,2],
                    sex = 
                     pheno$sex,
                    day = pheno $day)

ggplot(dataGG, aes(PC1, PC2)) +
      geom_point(aes(shape = sex, colour = day)) +
  ggtitle("PCA plot of the calibrated, summarized data") +
  xlab(paste0("PC1, VarExp: ", percentVar[1], "%")) +
  ylab(paste0("PC2, VarExp: ", percentVar[2], "%")) +
  theme(plot.title = element_text(hjust = 0.5)) +
  coord_fixed(ratio = sd_ratio) +
  scale_shape_manual(values = c(4,15)) + 
  scale_color_manual(values = c("darkorange2", "dodgerblue4", "forestgreen", "purple"))

pheno <- pheno %>% filter(stringr::str_detect(status, "female"))
counts <- counts %>% select(contains("f"))


design = model.matrix( ~ 0 + status, data=pheno)
colnames(design) <- sub("status", "", colnames(design))
y <- edgeR::DGEList(counts)
keep <- edgeR::filterByExpr(y, design)
y <- y[keep, ]
y <- edgeR::calcNormFactors(y)
v <- limma::voom(y, design, plot = F)

contrast <- limma::makeContrasts(
  day2_0 = female_2 - female_0,
  day2_all = female_2 - (female_0 + female_3 + female_5)/3,
  day3_0 = female_3 - female_0,
  day3_2 = female_3 - female_2,
  day3_all = female_3 - (female_0 + female_2 + female_5)/3,
  day5_0 = female_5 - female_0,
  day5_3 = female_5 - female_3,
  day5_all = female_5 - (female_0 + female_2 + female_3)/3,
levels = colnames(design))

fit <- limma::lmFit(v, design = design)
fit <- limma::eBayes(limma::contrasts.fit(limma::lmFit(v, design = design), contrast))

Efferocytosis genes

Day 2 vs Day 0

Day 2 vs all

Day 3 vs Day 0

Day 3 vs Day 2

Day 3 vs all

Day 5 vs Day 0

Day 5 vs Day 3

Day 5 vs all

Fibrosis genes

Day 2 vs Day 0

Day 2 vs all

Day 3 vs Day 0

Day 3 vs Day 2

Day 3 vs all

Day 5 vs Day 0

Day 5 vs Day 3

Day 5 vs all