Hi, I beg to disagree with the 'perceived wisdom', including just about everyone on this BB, but my answer is NO, there should be no bias - *provided* you do the subsequent refinement properly. First off, Rfree is useless as any kind of statistical measure of overfitting etc *unless* the refinement has converged to the point of maximum log likelihood against the current working set. So it's meaningless to say that Rfree is biased 'initially' i.e. *before* any further refinement is done using the new data because Rfree with the new data has no meaning at that point - it's neither biased nor unbiased, it's just meaningless! In any case why would one want to report an Rfree *before* refinement - what use is it?
So we can only sensibly talk about the Rfree values *after* the further refinement has converged - and if the refinement hasn't converged then Rfree bias is the least of your worries! So are people really saying that the Rfree at convergence using the new data is biased? For that to be true it would have to be possible to arrive at a different unbiased Rfree from another starting point. But provided your starting point wasn't a local maximum LL and you haven't gotten into a local maximum along the way, convergence will be to a unique global maximum of the LL, so the Rfree must be the same whatever starting point is used (within the radius of convergence of course). The other cures suggested such as SA and randomisation are IMO at best a waste of time and effort (i.e. it will take longer for subsequent refinement to recover from the shock to the system), and at worst likely to be worse than the disease they purport to cure. For example how do you know what RMS shift to use in the randomisation without causing the structure to jump into a local maximum LL: the resulting Rfree will certainly be biased then! There is of course a different issue (and maybe this is what is confusing some people) of comparing Rfree's from different test sets: we showed that this introduces a random relative error in Rfree of 1/sqrt(2*Nfree) (where Nfree = size of test set). However this effect is not bias, it's random sampling error. Cheers -- Ian > -----Original Message----- > From: owner-ccp...@jiscmail.ac.uk [mailto:owner-ccp...@jiscmail.ac.uk] On > Behalf Of Mike England > Sent: 24 September 2009 04:31 > To: CCP4BB@JISCMAIL.AC.UK > Subject: Rfree in similar data set > > Hi all, > > I will appreciate your comments on the following case: > > I have two datasets from the same or identical crystals. Initially, I > refine a structure against the first data set and later on switch to > another dataset for further refinements. > Do you think, my Rfree will be biased as Rfree reflections in second > dataset may be in fact Rwork reflections in previous datasets ? > > Thanks in advance, > > Mike Disclaimer This communication is confidential and may contain privileged information intended solely for the named addressee(s). It may not be used or disclosed except for the purpose for which it has been sent. If you are not the intended recipient you must not review, use, disclose, copy, distribute or take any action in reliance upon it. If you have received this communication in error, please notify Astex Therapeutics Ltd by emailing i.tic...@astex-therapeutics.com and destroy all copies of the message and any attached documents. Astex Therapeutics Ltd monitors, controls and protects all its messaging traffic in compliance with its corporate email policy. The Company accepts no liability or responsibility for any onward transmission or use of emails and attachments having left the Astex Therapeutics domain. Unless expressly stated, opinions in this message are those of the individual sender and not of Astex Therapeutics Ltd. The recipient should check this email and any attachments for the presence of computer viruses. Astex Therapeutics Ltd accepts no liability for damage caused by any virus transmitted by this email. E-mail is susceptible to data corruption, interception, unauthorized amendment, and tampering, Astex Therapeutics Ltd only send and receive e-mails on the basis that the Company is not liable for any such alteration or any consequences thereof. Astex Therapeutics Ltd., Registered in England at 436 Cambridge Science Park, Cambridge CB4 0QA under number 3751674
