If I understand you did a treatment to some cells and compared them with non-treated ones. Instead of running the four experiments at the same time, you did one treated and one untreated at a time. Then you did proteomics for each sample. Is the treatment the same in all four experiments?
Edit after the further comments of the OP: So, since the four treated samples are the same and the four untreated also (same conditions except from the treatment and the treatment is the same), then the way to go is as what your collaborator did.
Identification and quantification of the detected proteins is one thing and every sample of the four are replicates. Comparison between the two conditions is another thing.
The software he uses for ID can combine the same samples and already perform the statistical analysis, so the list you have now has higher credibility in terms of the proteins it includes and their levels for your cells when they are treated or not.
Using only one of your replicates, although it might give you different number of detected proteins or different amounts of each, has lower credibility, because it's only one sample out of four. In plain words, the presence or absence or the amount of a protein might be an artifact or insignificant.
What has to be clear is that the comparison between treated and untreated conditions is done after you have received the statistically correct list of detected proteins.
Thus, and in accordance to what I had said before the edit, if you take the list for each treated sample and compare them with any of the lists of the untreated ones, it will lead to conclusions that won't be as statistically significant as when you combine all treated together and all untreated together (as your colleague did). In plain words, your conclusions will have a higher chance to be wrong.
Every statistical analysis you do yourself for each sample should eventually lead to a similar consensus as your colleague got using the statistical analysis of his software.
As a sidenote, considering how many types of proteins are in a cell, now that you have a quite short list might not be a bad thing at all and you can proceed by:
- Concluding that the treatment had minor effect in the proteins that you expected it would affect (if they are not present in your lists as significant different)
- Trying to understand, identify and hypothesize on the role of the proteins that made it in your comparison threshold, as they have a much higher probability of being indeed different between the two conditions.
Splitting the samples in your analysis might have a point if the conditions of the experiment were not exactly the same or the treatment level is different etc. In that case you could split the samples accordingly, but that would definitely reduce your certainty level for your conclusions.