[BioC] Help on PLGEM R Package Usage

[Norman Pavelka]

Dear Qi,

Thank you for the data and the plots. I think the problem might reside
in your data. If you do a boxplot of your data you will notice that
they do not span many orders of magnitude. Here's how you can see for
yourself:

test <- log10(exprs(NSAFSet))  # log-transform your data
test[test == -Inf] <- NA     # to remove -Inf values coming from log10(0)
boxplot(test)

PLGEM fits best when data span several orders of magnitude, whereas in
your case the NSAF values only span two orders of magnitude. May I ask
you which proteomics technology you used to generate these data? Is
this a whole-cell extract or a subproteome?

Cheers,
Norman

On Sat, Sep 24, 2011 at 12:02 AM, Wu Qi <qwu at dicp.ac.cn> wrote:
> Dear Norman,
>
> Thanks for your quick response, please find my attached files and plot.
> I really don't understand how to optimize the arguments for every step and I
> have more than one dataset which also need evaluation. So could you possibly
> give me some advice on choosing arguments?
> The commands for generating this plot is as follows:
>
> library(plgem)
>
> NSAFSet<-readExpressionSet("exprs_NSAF.txt","phenoDataFile.txt")
>
> NSAFdegList<-run.plgem(NSAFSet, signLev=0.01, rank=100, covariate=1,
> baselineCondition="E", Iterations="automatic", trimAllZeroRows=TRUE,
> zeroMeanOrSD="trim", fitting.eval=TRUE, plotFile=TRUE, writeFiles=FALSE,
> Verbose=TRUE)
>
> plgem.write.summary(NSAFdegList, prefix="NSAF", verbose=TRUE)
>
> Kind Regards,
> Qi Wu
>
> -----Original Message-----
> From: Norman Pavelka [mailto:normanpavelka at gmail.com]
> Sent: Friday, September 23, 2011 11:38 PM
> To: Wu Qi
> Cc: bioconductor at r-project.org
> Subject: Re: Help on PLGEM R Package Usage
>
> Hi Qi,
>
> These fitting values look very outside the optimal range. Do you actually
> get a straight line in the ln(sd) vs. ln(mean) plot? If not, something might
> be wrong about how the data were normalized. You may e-mail me offline your
> data and/or the fitting evaluation plots and I might be able to diagnose the
> problem.
>
> The slope is one of the most important parameters to look at, and it usually
> should be between 0.5 and 1. The r^2 and Pearson correlation coefficients
> should be as close to 1 as possible.
>
> In order to capture the plots in another file format you can call
> pdf() prior to run.plgem() to generate a high-quality vector-graphics PDF
> file. Example:
>
> library(plgem)
> data(LPSeset)
> pdf()      # this will open a new PDF file called 'Rplots.pdf'
>           # in your current working directory plgemOutput <-
> run.plgem(LPSeset)
> dev.off()  # this will close the PDF file
>
> Instead of pdf() above you can try bmp(), jpeg(), tiff() or virtually any
> other major image file format. Under Windows there is also
> win.metafile() that generates EMF image file format.
>
> Hope this helps!
> Norman
>
> On Fri, Sep 23, 2011 at 11:06 PM, Wu Qi <qwu at dicp.ac.cn> wrote:
>> Dear Norman,
>>
>>
>>
>> Thanks for your further advice.
>>
>> After applying the arguements you recommend, The parameters for my
>> NSAF dataset are: slope=0.291, intercept=-5.35, adj.r2=0.636,
>> Pearson=0.464. Are they horrible?
>>
>> Could you tell me which is the most important parameter to assess my
>> dataset quality?
>>
>> And how can I export high quality figure (emf format) with these
> parameters?
>> I could only find it in the simplest wrapper mode. When I append
>> "plotFile=TRUE" in run.plgem function, I could only get a png figure
>> whose resolution is really poor.
>>
>>
>>
>> Best Regards,
>>
>> Qi Wu
>