The plots output will depend on the type of analysis and input parameters. The titles and labels of the plots are largely self-explanatory. Possible plots include:

- Control Vs. Experimental Scatterplots (before and after normalization).
- Plots of standard deviation of the expression levels versus the corresponding mean, visually answering the question: Is there more variation at higher values of expression? This is done for different conditions and normalizations.
- A Receiver Operating Characteristic (ROC) curve which depicts the tradeoff between
false positives and true positives when choosing a
*p-*value threshold for PPDE.

There are two plotting options:

- Plot using density estimate smoothing : Plots will have data binned and colored to show smooth density estimates. This allows the user to see the distribution of the data.
- Remove outliers: Produces plots where outliers (more than 2 IQR above or below the 1st or 2nd quantiles, respectively) have been removed. This allows the user to see the true relationship by plotting most of the data in a reasonable scale.