Absolute logfc and Pvalue for statistical calculation

Question

[anasjamshed]

I am doing differential gene expression analysis based on 6 geo-series and using this measure to make a volcano plot based on 10 shared genes.

p_cutoff <- 0.05
fc_cutoff <- 1

DC_top_genes <- DC_top_genes %>% 
  mutate(Significant = adj.P.Val < p_cutoff, abs(logFC) > fc_cutoff )  %>%   
  mutate(GENE_SYMBOL = ifelse(GENE_SYMBOL %in% targe_gene_symbol_entrez$SYMBOL, 
                              GENE_SYMBOL,""))

head(DC_top_genes)

dc_volcano <- ggplot(DC_top_genes, aes(x = logFC, y = -log10(P.Value), col = Significant, label = GENE_SYMBOL)) +
  geom_point() +
  geom_text_repel(col = "black", max.overlaps = 1400) +
  theme(
    plot.background = element_rect(fill = "white", color = "white"),  # Set background to white
    plot.title = element_text(hjust = 0.5, vjust = -0.5),  # Adjust title position inside the plot
    plot.margin = margin(20, 20, 20, 20)  # Adjust margin to make space for the title
  ) +ggtitle("Dilated Cardiomyopathy vs Control")  # Add title inside the plot

Should I change fc_cutoff or completely remove it?

[Ram]

to make a volcano plot based on 10 shared genes.

What does this mean? You make a volcano plot from DE results based on all genes, not a random subset you pick.

[anasjamshed]

yes but my target genes are : "ACTN2", "CRYAB", "BMP10" "CSRP3", "DES", "FHOD3”, “FLNC", "LDB3", "MYZAP", "MYPN", "MYOZ2", "NEXN", "PDLIM3", "PDLIM5", "TCAP", "TTN."

[Trivas]

So is this microarray or qPCR data? If you're trying to highlight those specific genes on a volcano map, that's a different story.

I've never seen a mutate command written like this: mutate(Significant = adj.P.Val < p_cutoff, abs(logFC) > fc_cutoff ). Surely it should be & instead of a comma.

[anasjamshed]

this is microarray data