Hello all,

I am trying to find my way through the different interpretations and
calculations of the FDR, but I'm a bit lost where it comes to the
PeptideProphet.

So far, I know that the simplest calculation is (decoy_hits/
target_hits). So, I ran X!tandem on my dataset (target DB +
concatenated decoy DB) and then ran PeptideProphet on the resulting
pep.xml file (not setting the decoy option!).
I then set a certain probability threshold (say 0.85) and looked at
the number of spectra (e.g. 1200 of 1500). Setting the protein text to
decoy gives me, e.g. 50 hits. The FDR for a prob. of 0.85 would then
be 50/1150. If I look at the table displayed in the PeptideProphet,
the FDR I found is almost spot-on with the number in the table. The
thing is that if I lower my probabilty threshold, the FDRs in the
table stay relatively low, while the FDRs I calculate with the above
formula go up. Is there any extra correction being done in the
PeptideProphet (like correct for the percentage of incorrect target
hits (PIT) as described by Kall et al in 2008)?
Or am I missing something vital here?

Furthermore, how is the estimated number of correct assignments
calculated? I can't seem to find the correct formula to come to that
number? I assume it is related to the surface under the curve plotted
with the correct identifications?

Many questions, but I hope someone can help me with this.

Best regards,

bjorn

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