Did you every consider what effect in-source oxidation might have on the mass shifted decoys? For z = 2, an 8*1.0005 Th mass shift is about the same as an oxidation (+- 10-20ppm)

Very cool figure! I understand that N*1.0005 mass shifts are used due to the distribution of possible peptide masses.

We only need to assume that an incorrect transfer for a given donor peak is equally likely to involve the predicted RT as it is to involve the random RT.

That's a good point! There's a chance (I would argue a small chance) that you could randomly choose an RT and end up with an accurate match.

However, we don't rely on the assumption that every single random-RT peptide is an incorrect match.

The and Kall use a 5*1.0005 Th shift because they expect there to be peptides at the shifted m/z.

"The idea behind this offset is that the density, w.r.t. precursor m/z and retention time, of MS1 features is approximately the same in this offset region."

A match is false if the two peaks were generated by different analytes. We can't really "guarantee" that a match is false. We only assume that an incorrect match for a given donor peak is equally likely to involve the predicted RT as it is to involve the random RT

I don't think those assumptions are necessary (or true). When we investigated potential features, we found that XIC shape doesn't have a lot of predictive power. Most peptides have approximately Gaussian peaks. Likewise. the isotopic distribution for peptides with similar masses don't really differ

"In this case 11 Da was chosen as a randomly selected integer value which differs from any known common post-translational modification. Indeed the number of matches does not vary significantly as long as the mass shift value stays an integer" - Petyuk et al., 2007

In the original work from PNNL, an 11 Da shift was used as this mass difference doesn't correspond to any common PTMS or tags. However, if you look at the human proteome, there are a lot of peptides that are 11 Da away from one another.

We would love to look at more single-cell datasets, but our method for FDP estimation only works with specialized "two-proteome" experiments. It would be great if our method catches on and more of these datasets are generated!

The randomized RT we use when trying to locate a decoy peak has to be different from the RT of the target donor peptide. This ensures we don't select the target peak twice. Then, at the end of the peak-matching procedure, we go through all peaks and make sure none were assigned to multiple peptides

It's easier to find decoys, because RT is a more continuous variable. We consider one continuous RT range, instead of looking at discrete points in m/z space and iterating until we find something.