Hi all,

I'm quite new to using DESeq2 and was hoping for some guidance. I appreciate my question might be very basic - apologies for this.

I have an experimental set of six groups (24 samples in total, n = 4) and am looking at creating different comparisons. I've read the DESeq2 vignette and have made my contrast like so:

 dds <- DESeqDataSetFromTximport(Txi_gene, colData=sample_file, design=~group)
 dds <- DESeq(dds)
 dds$group <- factor(paste0(dds$condition, dds$time))
 design(dds) <- ~ group

res1 <- results(dds, contrast=c("group","A_day14","B_day14"))
res2 <- results(dds, contrast=c("group","A_day14","A_day0"))

*etc.*

This all seems to be looking as expected. My next question is about visualizing the differentially expressed genes: if I'm looking at comparison A vs B, how can I extract just those DEGs rather than the genes in general?

This is my code chunk so far:

normalized_counts <- counts(dds, normalized=TRUE)

normalized_counts <- normalized_counts %>% 
  data.frame(check.names=FALSE) %>%
  rownames_to_column(var="gene") %>% 
  as_tibble()

top50_sigRes1_genes <- res1_lfcshrink_tb %>% 
        arrange(padj) %>% 
        pull(gene) %>%
        head(n=50)

top50_sigRes1_norm <- normalized_counts %>%
        dplyr::filter(gene %in% top50_sigRes1_genes)

gathered_top50_sigRes1 <- top50_sigRes1_norm %>%
  gather(colnames(top50_sigRes1_norm)[2:25], key = "samplename", value = "normalized_counts")

My hunch is that I need to change the [2:25] to reflect only the columns I'm interested in per comparison? So if I look at A vs B, I only select those columns and disregard C, D, etc. However, when I try that I get the error ! incorrect number of dimensions.

So for visualization:

gathered_top50_sigRes1_joined <- inner_join(meta_data, gathered_top50_sigRes1)

ggplot(gathered_top50_sigRes1_joined) +
        geom_point(aes(x = gene, y = normalized_counts, color = group)) +
        scale_y_log10() +
        xlab("Genes") +
        ylab("log10 Normalized Counts") +
        ggtitle("Top 50 Significant DE Genes - A day 14 vs B day 14") +
        theme_bw() +
    theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
    theme(plot.title = element_text(hjust = 0.5))

This gives me a nice plot, but all my samples are included in it so it's not specific to the comparison I'm looking at.

I hope my question makes sense and thank you in advance for taking the time to help me!

I got the answer to my question here: https://www.biostars.org/p/9516797/#9516956