DESeq2 Visualizer

This tool creates interactive visualizations of DESeq2 differential expression analysis results, showing a MA plot, Volcano plot, and dispersion plot with linked interactions. By default, the tool loads a sample DESeq2 results file from the pasilla dataset. You can also upload your own data or generate random data for demonstration purposes. Instructions for creating your own input files are at the bottom of this page!

This page works best on a desktop device. The plots may be too small to effectively use on mobile.

Visualize Your Own Data

How To Generate Input Data from DESeq2

The visualization accepts a CSV file with the following columns:

• gene_id: Gene identifier
• baseMean: Base mean expression
• log2FoldChange: Log2 fold change
• pvalue: Unadjusted p-value
• padj: Adjusted p-value
• lfcSE: Log fold change standard error
• stat: Statistical test value
• dispersion: Dispersion value (optional)

You can generate this file using the following R code:

# Load DESeq2 library
library(DESeq2)

# Assuming you have a DESeqDataSet object called 'dds'
# and have run DESeq analysis:
# dds <- DESeq(dds)

# Get results
res <- results(dds)

# Add gene IDs and dispersion values
res$gene_id <- rownames(res)
res$dispersion <- dispersions(dds)

# Write to CSV
write.csv(res, "deseq2_results.csv", row.names = FALSE, quote=FALSE)