I uploaded an example dataset with this issue. It is in
/incoming/MAJOR_LAB_UNC_MA145.zip

On Mon, Oct 3, 2011 at 6:27 PM, SPCTools Admin <[email protected]>wrote:

> Hi Dennis,
>
> This should not happen and it indicates a problem with running the
> algorithm on your dataset.  Do you still see the message when you
> disable the option to force the distribution fit?  This is an option
> that should be used for troubleshooting only and is not expected to
> generate good results.  If you can package the dataset and post to our
> FTP server I can debug the issue further.  Instructions for posting
> data to FTP can be found here:
>
> http://tools.proteomecenter.org/wiki/index.php?title=TPP:Frequently_Asked_Questions#How_do_I_upload_files_to_the_SPC_tools_team.3F
>
> -David
>
>
>
> On Oct 3, 8:49 am, Dennis Goldfarb <[email protected]> wrote:
> > Hi,
> >
> > Every once in a while I receive an error stating:
> >
> > Iterations: .Assertion failed: idx < posProbs_->size(), file
> > Validation/InterProphet/InterProphetParser/KDModel.cxx, line 143
> >
> > As far as I can tell this means that there aren't enough likely true
> spectra
> > to properly model the true and false distributions. Is this the correct
> way
> > to interpret the error? In the past I've only seen it when the # of decoy
> > hits is almost the same as forward hits, so that makes sense to me.
> Lately
> > I've had this error pop up when there are thousands more forward hits
> than
> > decoys, but only if I use the accurate mass binning model. The program
> > executes fine and the results look great (3000+ peptides of bait) without
> > accurate mass binning. We have an orbitrap and I haven't had this issue
> in
> > the past. Could this be a sign that our instrument's accuracy is slipping
> > and needs reconfiguration/maintenance? Could someone give me an idea of
> how
> > severely the accurate mass binning model penalizes the mass difference?
> >
> > I'm using TPP v4.5.0 on a Windows 7 Machine. I've tried combinations of
> > forcing the distribution fit, and using non-parametric distributions.
> >
> > Thank you,
> >
> > --
> > Dennis Goldfarb
> > Graduate Student
> > Department of Computer Science
> > University of North Carolina at Chapel Hill
>
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-- 
Dennis Goldfarb
Graduate Student
Department of Computer Science
University of North Carolina at Chapel Hill

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