Alexander,

I don't have a direct answer to your question, but I can confirm that we found this software sometimes to be buggy, too. If the support team cannot help you, you may consider to use Skyline software from Mike MacCoss' lab to calculate your XICs. We have better experiences with that.

Sonja

You can have a look on thermo omits portal as we (and others) had a similar problem when using PD 1.4 (https://portal.thermo-brims.com/index.php?option=com_discussions&view=thread&catid=4%3Aproteomics-forum&thread=2252%3Amissing-precursor-ion-area-detector-values&Itemid=54 and http://portal.thermo-brims.com/index.php?option=com_discussions&view=thread&catid=4%3Aproteomics-forum&thread=2277%3Aprecursor-ion-area-detector-area-calcualtion-problem&Itemid=54). We had only some peptides with missing values. Also, from what I know, PD 1.4 can display a precursor area information for a protein (with Precursor ions area detector node) only from the average of top 3 most abundant peptides, even if those peptides are not unique and until now, I did not find any option to modify this. You could also use MaxQuant, a program that can report the intensity, LFQ and iBAQ value for a protein and you can choose what peptides to consider for quan (unique, razor, modified, unmodified etc.) or Skyline as Sonja suggested.

Regards,

Cristian

Thank you, Sonja and Cristian for your answers. It appears Service Pack 1 of PD1.4 partly solves this issue. It generates peak areas for most of the peptides now.

However, some peptides still have no peak areas for some reason while multiple PSMs of other peptides show different areas, where they should be the same. I have taken this issue to the Thermo omics portals now.

I could be wrong, but I believed MaxQuant was only suitable for labelled quantification and we do not use labelling in our experiments. Also, I have not been able to do this in Skyline could anyone point me to a guide or tutorial on how to do that?

Thanks for the help!

Dear Alexander,

I would be interested in solving the problem of missing precursor area for some peptides in PD 1.4 as I have no definite answer for this (https://portal.thermo-brims.com/index.php?option=com_discussions&view=thread&catid=4&thread=1972&Itemid=54).

Regarding MaxQuant, the program was initially developed for SILAC based experiments, but at this moment does have support also for label-free experiments (http://www.maxquant.org/faq.htm) and a paper with label-free (http://www.cell.com/immunity/abstract/S1074-7613(10)00044-0), but there also others.

I do not have any experience in using Skyline so perhaps Sonja can help you with a tutorial.

Regards,

Cristian

Hi Christian,

I have attached 3 screenshots of typical problems. You can see a lot of missing areas in the screenshots.

The first screenshot shows a missing area with a generally bad XIC. I have quite a few of them, to be honest, and I do not realy know if XICs like these are common or not. Are these peptide id's trustworthy or are these typical false positives?

Second screenshot shows a good XIC with still no calculated area. Usually, XICs like this give good areas, but some still don't.

Last screenshot shows a peptide (KVLAIDHLNEDQLR) which is probably "sticky" as it has multiple samplings. There are a lot of instances (mainly in the large shoulder) that causes it to not calculate an area, but there are also a lot of calculated areas which differ from each other.

Do you recognize these problems? I read your topic on thermo-brims. Did you get any useful information from the thermo staff?

Last question: do you work with or without peptide grouping? How does PD calculate the peptide "area" from all relevant PSMs when peptide grouping is on?

Alexander

Dear Alexander,

From what can I see is that in the first screenshot you have a peptide with a strange elution profile. I also had this kind of elution profiles from sticky peptides, actually peptides that were high abundant in my sample. Peak broadening and also peak tailing is common for this kind of peptides and also it depends on the column type, the gradient that you use, etc. For example, on a nano-LC with a 10 cm Proxeon nano column I get 45 sec-2 min usually on peptides in longer gradients (120 min or longer), but for nano-UPLC usually the peak width is narrower. I would be curios to see the #PSMs in sample B3 compared with E3 or F3, where for the same sequence (KKEEEELVSLKDR) you have a value for the precursor area. For the false-positive part, I know that Percolator (I think you used Percolator for peptide validation) tends to overestimate some of the ID's (I had good id's with only 1-2 peaks matched from MS/MS), but in general working on a 99% confidence should be okay. You can read more (http://proteomicsnews.blogspot.ro/2013/10/how-does-percolator-affect-msamanda.html).

Regarding the missing value for XIC I did not get an exact answer for my problem, because I had a non-tryptic peptide and in the end they advised me either to manually get the XIC (my problem was that I had missing values for XIC and my peptide was unique, SequestHT reported the peptide as non-unique with low confidence) either to use PEAKS with de novo option.

Regarding peptide grouping I personally do work with peptide grouping ON by default. However it also depends on how you do the peptide grouping. In PD 1.4 you have the option to set peptide grouping by mass and sequence or only by sequence. I work usually with peptide grouping by sequence as I want to do some differential analysis for multiple samples (https://portal.thermo-brims.com/index.php?option=com_discussions&view=thread&catid=4&thread=2228&Itemid=54 and https://portal.thermo-brims.com/index.php?option=com_discussions&view=thread&catid=4&thread=2316&Itemid=54). If I remember correct from training I think PD1.4 should report the highest value in the peptide group from all PSMs no matter the charge (see screenshot). You can check this on several sequences.

Regards,

Cristian