Peak integration wrong for a single replicate, but for thousands of precursors | joshuasmith | 2023-03-07 |
Hi all, I am having an issue where Skyline is integrating peaks incorrectly for one out of 6 replicates, but for thousands of precursors in the file. This is data from the same support ticket as a previous issue with importing the DIA-NN spectral library (https://tinyurl.com/2x326w3a) - thanks Nick for helping on that. I've attached screenshots of the issue. I have tried refining the peak picking several times and I think I have a really good peak scoring model, but it still is mis-integrating peaks. Sometimes it does pick the correct peak (slide 4), but this is uncommon. I obviously would prefer not to have to manually go through roughly 10,000 precursors and correct integration on what appears to be 80-90% of them. One way I tried to do this more quickly was by looking at run-to-tun regression and finding outliers, but this didn't work. As you can see in slides 5-8, as highlighted with the red box on the regression plot, there isn't much deviation for the misintegrated peaks, and so no good way to target the worst cases first. It's so many anyway that it wouldn't end up being a "targeted" fix. One thing I did notice is that the replicate that has a lot of integration issues does seem to be unusual in that it has more ID matches for than other replicates, and they tend to skew towards the leading tail of the peak. See slides 8-10. Could that be the issue? Not sure why that would have happened, other than that was the first sample in the file list run through DIA-NN. The spectral library is based on all 6 runs, but the DIA-NN log does say: I have compressed my entire skyline document and can share that if needed, although it's 4 Gb zipped. |
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