Could we be overthinking how to adequately compensate for quantification compression in reporter ion quan data?
This study from Erik Ahrne (sorry, I don't know how to make the correct symbols above your name) et al., seems to think so, and they've got a simple solution to tell us about in JPR here!
In this work they take a step back and say...reporter ion quan compression? Maybe we should just recalibrate and compensate for it! They do this by testing a bunch of different calibration standards -- finally ending up on a nice 6 protein mixture that they dilute out and spike into each channel.
Effectively they now have a calibration standard inside their runs. If they compare the ratios of what they get experimentally to what they know they spiked in -- BOOM! -- they have an idea of the compression ratio that their mix suffers from.
For example -- If their 4:1 protein comes out of processing at 2.132: 1 then they can do some simple math to readjust their values back out.
It seems to work well, too! They do some E.coli and a human cancer cell line extract in both cases they pull out evidence that it is helping. They also take a complex set and do an elaborate label free quan work up on the samples and show that adjusting the TMT gets them closer to the LFQ. To make this even more thorough, they show it helps when doing TMT with an Orbitrap Elite and with a QE HF (both of which, I might add, appear to have been ran by someone who knew what they were doing. Nice methods!)
They've already made the package to do these adjustments available in the SafeQuant R package. But they are quick to point out you could do this adjustment yourself in Excel.
Curious how their adjustment scheme compares to yours (you smart variance stabilization people, I'm looking at you...though I'm almost as curious about significance and/or S/N adjustments...) well, this topnotch group already posted this dataset on PRIDE -- it is PXD003346.
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