Just to clarify and add some detail: if I run XPress twice on the same
(very large, multi-sample) pepXML file, once with proper arguments for H/L
(8Da separation) and once with proper arguments for M/L(8Da separation),
and then I compare the logs of the light areas determined with the two
methods, PSM by PSM, I get a correlation coefficient of 0.87. The great
majority of the light areas are exactly the same between the two XPress
runs, but a large minority are far off-diagonal.

For this reason, I would not expect H/M ratios derived from the H and L
areas from those two runs to behave similarly to H/M ratios somehow
calculated from a single XPress run.

On Fri, Jul 3, 2015 at 1:40 PM, Damon May <[email protected]> wrote:

> Thanks for the response, Amit. Sorry, I'm not sure what you mean by
> "correlation for only those ratios where all three labels (L M H) are
> present". By definition, I'm only comparing ratios that were present as H/L
> in one XPress run and M/L in the other (and so L M H are present in one run
> or the other). Do you mean ratios where all 3 labels have PSMs? That seems
> a bit stringent.
>
>
> It's not that I expect the quantitation to suffer when I ignore the light
> label. It's that, demonstrably, when I compare the heavy from a H/L XPress
> run and the light from an M/L run, I get very different results from the
> H/L run's ratio. Meaning that, presumably, the L quantity that's measured
> is varying significantly across the two runs. For that reason, I expect the
> H from the H/L run also to be difficult to compare with the M from the M/L
> run.
>
> MaxQuant might be the better option for me. Thanks for the suggestion!
>
> Damon
>
> On Fri, Jul 3, 2015 at 8:52 AM, Amit Yadav <[email protected]> wrote:
>
>> Hi Damon,
>>
>> Have you tried checking the correlation for only those ratios where all
>> three labels (L M H) are present?. The reason could be that finding any two
>> pairs may have higher chances of false positives which may be distorting
>> your real ratios and therefore resulting in low correlation.
>>
>> Since you wanted H/M, why do you expect quantitation to suffer when you
>> ignore light label?
>>
>> I don't have idea about this mutilation trick.
>>
>> If possible, a triple SILAC search can be done with ProteinPilot and any
>> ratios can be calculated even post search (M/L, H/L, H/M or any other
>> combination)
>> In freely available software solutions, MaxQuant can be used.
>>
>>
>>
>>
>>
>>
>> On Friday, July 3, 2015 at 6:07:12 AM UTC+5:30, Damon May wrote:
>>>
>>> I've got triple-labeled data, heavy-medium-light K. We've discussed
>>> before the possibility of supporting this type of data fully, and I know
>>> that's not possible yet.
>>>
>>> However, I would like to compare medium with heavy (specifically, I'd
>>> like to assess M/(M+H)). This is only a comparison of two quantities, but
>>> I'm having a hard time figuring out how I might do it with XPress.
>>>
>>> I tried running XPress twice (H/L and M/L) and using the values for H
>>> from one run and M from the other. That did not behave well at all, and
>>> when I sanity checked by comparing H/L ratios derived from one XPress run
>>> with H/L ratios derived from the H from an H/L run and the L from a M/L
>>> run, the low correlation (~0.3) made me realize that I should not expect
>>> this to work well.
>>>
>>> I considered re-running Comet, pretending that there's no light label,
>>> and running XPress on the results. This would certainly "work", but I would
>>> lose quantitation from all PSMs in which only the light was identified;
>>> that's likely quite a lot of peptides.
>>>
>>> My only other idea is to mutilate the PepXML from my current (L-M-H)
>>> Comet searches, dummying them up so that it looks like I ran an M-H only
>>> search, and creating dummy M or H IDs for everything that's currently an L
>>> ID. That's a really ugly solution, though, and I'm worried it'll fail for
>>> some reason I haven't thought of.
>>>
>>> Can anybody think of another way to do this?
>>>
>>> Thanks,
>>> Damon
>>>
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