you should use match between runs if and when the samples are similar. match between runs uses the retention time and m/z values of an ID and looks for it in other samples, assuming that the samples are similar, to alleviate sampling issues in DDA. if you have a (good) pulldown, your control and IP should be very different, as are various conditions. in this case, you might have false positive due to incorrect fitting or noise.

you should look at the chromatograms to see how different are the conditions as well as look at the ID's. you might need to process the samples more than once, in this case.

David Morgenstern the samples are different from each other. They’re in duplicate but each pulldown has a different oligo and are either treated or not treated. The controls for each are different, so when I was processing my data initially, I didn’t use match between runs because of this. Would that be the correct way to go about it?

I would begin the way you did it, and look at the results. if the ID's overlap by more than 60%, you might want to try MBR and see what happens. but generally speaking - yes, you did it as I would.

the problem with IP's is that too often they have 1000-2000 proteins identified in them (due to experimental issues) and that's where you'd need MBR.

Thank you David Morgenstern

Rebecca Ruggiero p.s. you might also want to avoid using the LFQ and use the intensity values. LFQ normalization assumes normal distribution of the data, which isn't the case in IP.

David Morgenstern Could I also use LFQ intensities but skip normalization?