What kind of conclusions is possible to take from volcanoplots. Only the visual apperance of thel number of deexpress or super express genes?
What kind of conclusions is possible to take from volcanoplots. Only the visual apperance of thel number of deexpress or super express genes?
I like volcano plot's visualization, It gives over view of fraction of differentially expressed genes compared with total number of genes. You can subset your data with p-value threshold and Fold change threshold, and annotate your upper right and upper left genes on the plot. Then you can go for Gene-set enrichment or ontology with annotated ones and could give total genes in plot as background.
you can consider this as answer also to your post.
Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
A volcano plot as long as it is not interactive gives only an overview about the data. It is basically a scatter plot of fold change and p-value.
It is a nice visualization of the data, but without a list of the significant genes nothing more.
Thanks linus. I was seeking this kind of answer.
http://en.wikipedia.org/wiki/Volcano_plot_(statistics)