Hello Shagun,
I noticed in your condition file you are using TMT10 with the following
masses:
<reagent mz="126.127726" />
<reagent mz="127.124761" />
<reagent mz="127.131081" />
<reagent mz="128.128116" />
<reagent mz="128.134436" />
<reagent mz="129.131471" />
<reagent mz="129.137790" />
<reagent mz="130.134825" />
<reagent mz="130.141145" />
<reagent mz="131.138180" />
The difference between neighboring channels is <0.01 at the lowest and yet
you are using tolerance of 0.2:
<massTolerance value="0.2" />
I think the appropriate mass tolerance for this type of labeling should be
~0.001.
Does that make sense? Please try running Libra with the mass tolerance
appropriate for this type of label.
Cheers,
-David
On Fri, Mar 25, 2022 at 10:34 AM Shagun Gupta <[email protected]> wrote:
> Hi David
>
> Could you suggest a good email to reach you with? I can share the
> pep.xml's and Libra condition file that way?
>
> -Shagun
>
> On Friday, March 25, 2022 at 11:00:38 AM UTC-4 David Shteynberg wrote:
>
>> Hello Shagun,
>>
>> Thank you for your email and interest in the TPP. I have recently been
>> comparing TMTPro analysis by ProteomeDiscoverer and Byonic to that produced
>> by TPP's Libra. As far as I can tell, when I run and compare the
>> quantities (intensities) they are mostly the same between Libra (without
>> isotopic impurity correction and 0 pseudocounts) and the
>> ProteomeDiscoverer/Byonic. Execution of Libra is defined in the
>> conditions.xml file that has to be defined for each Libra run. I would be
>> happy to take a look at your data and analysis to see if it can be placed
>> on the right path for the Libra analysis to work. Please post your results
>> somewhere I can download and test.
>>
>> Cheers,
>> -David
>>
>> On Fri, Mar 25, 2022 at 6:36 AM Shagun Gupta <[email protected]> wrote:
>>
>>> Hello
>>>
>>> Our lab has been trying to use Libra to quantify MS2 (Ion-trap)
>>> identification and MS3-based quantification of TMT datasets and we were
>>> trying to benchmark with an artificial yeast and mammalian spiked dataset
>>> with known fold-change (FC) values. However we observe drastically
>>> different values than expected, something we don't observe with other
>>> search engines for the same dataset.
>>>
>>> Has this issue been encountered before/ is there something obviously
>>> wrong when running with TPP that might cause this? Happy to provide further
>>> details on the dataset and parameters used to run with (most of them
>>> default apart from additions like static modification for TMT and
>>> specification of MS3 for quantification among others).
>>>
>>> Thank you,
>>> Shagun
>>>
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