On Wed, Nov 2, 2011 at 1:17 PM, Smith, Hilary A <hilary.smith@gatech.edu>wrote:

> Hello,
> I'm a graduate student and just starting to analyze my first set of
> RNA-Seq data (so learning R/Bioconductor). In using the baySeq program, I
> am slightly confused about how to color-code the significant values in the
> plotPosteriors (and plotMA) functions.
>
> The vignette includes the example below to color-code differentially
> expressed genes as red.
> > plotPosteriors(CDPost.NBML, group = 2, samplesA = 1:5, samplesB = 6:10,
> col = c(rep("red", 100), rep("black", 900)))
>
> However, I believe the use of 100 for the red (and 900 for the black / not
> differentially expressed) is specific to their simulated data set. Is this
> correct, and if so, how can I make the function more general to plot the
> differentially expressed genes for any data set?
>
>
Your belief is correct.  The data in the vignette were set up so that the
first 100 rows were differentially abundant between two groups of
libraries.

The objective of making the function "more general" as you pose is somewhat
complicated.  You could add a threshold parameter and have plot render the
entities differently depending on the relationship of the posterior
likelihood to the threshold.  That is not really making it more general,
but it is adding features and complexity.  You might want to consider how
to embellish the plot post hoc with information concerning decisionmaking
about differential abundance.

To get a sense for issues involved in choosing or conveying the effect of
choosing a threshold, just plot

 plot(CDPost.NBML@posteriors[,2])

and consider the sensitivity and specificity of any threshold given what we
know about the simulation.



> Thank you,
> Hilary
>
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