The function creates a 'four quadrant' volcano plot, where the FDR and log2FoldChange thresholds dictate the significant up-regulated category, the significant downregulated category, the significant low regulation category and the non-significant category
Genes of interest are labeled in a rectangle for visibility and will have the same color as the category in which they are in. Top significant genes are also labelled in rectangles but will have black text in order to distinguish them from the genes of interest
The plot is created using ggplot2, to save a plot the ggsave() function is recommended It is also recommended to use the following parameters to save the plot. dpi=300 width=21 height=19 units='cm'
volcanoplot_alt(
DE_res,
genes_of_interest = c(),
filter_choice = "padj",
l2FC_thresh = 1,
p_thresh = 0.05,
plot_title = "Volcano plot",
label_top_n = 0,
show_non_sig_interest = TRUE
)The differential expression results to be plotted
A vector containing gene names to be labelled in the plot To not label any genes, leave as default or provide an empty vector.
Either padj or pvalue, the choice will be used to filter for significance
The log2FoldChange threshold used to establish significance
The pvalue or padj threshold used to establish significance
The title to be give to the plot
The number of genes to label. Genes will be taken in order of significance where the genes with the lowest adjusted p-value are taken first.
A boolean to indicate if the non-significant genes of interest should be shown.
The ggplot object for the volcano plot
TS_object<-create_example_object_for_R()
TS_object <- normalize_timeSeries_with_deseq2(time_object=TS_object)
#> converting counts to integer mode
#Perform conditional differential gene expression analysis
TS_object<-conditional_DE_wrapper(TS_object,vignette_run=TRUE)
DE_res<-slot(TS_object,'DE_results')$conditional$IgM_vs_LPS_TP_1$DE_raw_data
v_plot<-volcanoplot_alt(DE_res = DE_res)