Hi Gabriella,

I’m not an expert on Percolator (or machine learning) but I think the problem 
is simply that the dataset is too small. There are only 128 results, which need 
to be split into training and cross-validation test sets, and thus there isn’t 
much data to train or test the models. Manually looking at the results show 
some PSMs to be highly likely to be correct, but Percolator requires a lot more 
PSMs to perform its analysis correctly (a limitation of this type of validation 
approach).

 

An option you have would be to combine your intra and inter protein Kojak 
results into a single dataset to give Percolator. Likely, you have a lot of 
intra-protein PSMs. Both of these result sets have the same parameters for 
Percolator and thus they can be combined, even if it is not the most ideal 
approach. Combining intra and inter protein PSMs can be done with cut-and-paste 
in Excel or a text editor. Just make sure you have only one header line at the 
top of the file.

 

Cheers,

Mike

 

From: spctools-discuss@googlegroups.com 
[mailto:spctools-discuss@googlegroups.com] On Behalf Of Gabriella Gellen
Sent: Thursday, November 08, 2018 7:15 AM
To: spctools-discuss
Subject: [spctools-discuss] Percolator stopped working using Kojak result files

 

Hi Everyone,

 

I'm quite new to Percolator and now I am practicing with data, that has already 
been published to have crosslinks using Hekate ( 
<https://www.ncbi.nlm.nih.gov/pubmed/24010795> 
https://www.ncbi.nlm.nih.gov/pubmed/24010795). I am trying to validate the 
crosslinked results found by Kojak 1.6.1 using Percolator 3.02. However, the 
program stopped working, and I got no results. It says "Warning: No 
target-decoy protein pairs found for the picked protein strategy.

  Check if the correct decoy pattern was specified with the -P flag;

  if the target protein is called "protA" and the decoy protein "decoy_protA", 
use the option "-P decoy_"."

But the settings for the decoy pattern were correct.

What do you think can be the problem for this?

 

Thank you for your help in advance,

 

Gabriella

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