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.