We have an awful lot of search engines these days and we have almost as many (more?) ways of working out our automatic false discovery rates. The Qu lab seems to have stepped back and said, let's try to sort it out, meaning, which FDR is more appropriate for large datasets -- and when?
This is a heavy analysis of three different search engines available for running in or through Proteome Discoverer as well as an analysis of what false discovery rate algorithm/method or filter will leave you with the best possible results. Interestingly, the answers appear to be very analyzer and fragmentation-type dependent.
I'll leave this here for you guys who took more maths! The answer appears to be...there is no easy answer...these are things we're definitely need to spend more time working on as proteomics moves further and further into the BIG DATA world.
You can find the abstract for this (paywall) paper here.
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