A Sectioning and Database Enrichment Approach using FragPipe

[BPGA]

Hello,

Thank you so much for creating this great pipeline! I have been trying to use FragPipe for protein identification in metaproteomics data. The approach I wanted to use is the "Sectioning and Database Enrichment Approach," in which I have to create a small subset of my reference database and search for proteins in each subset without using any FDR. Then, I will create a final database using all the proteins identified in the primary search and rerun FragPipe, this time with a 0.01 false discovery rate (FDR). My question is, how do I use FragPipe without considering the false discovery rate (FDR) during the primary search?

The approach I am trying to use is explained in the paper: https://pubs.acs.org/doi/10.1021/acs.jproteome.0c00260

Thanks so much!

Vinod

[fcyu]

Hi Vinod,

If I understand correctly, it is exactly what we are working one. We have a prototype module that can do that. Will let you know when the pre-released version of FragPipe is ready to test.

Best,

Fengchao

[BPGA]

Thanks so much for your prompt response, Fengchao! Yes, that would be great! Until then, is there any way that I can do it myself by changing some parameters that do not consider FDR in the first step, and then I can combine all the proteins and rerun FragPipe with FDR? Alternatively, I can use a two-step approach, as described in this paper: https://doi.org/10.1002/pmic.201200352.

Could you please tell me what I should change in the default parameters that do not consider FDR in the first step?

Thank you so much!

-Vinod