Hello again, Back in 2001 people still remembered the difference between Rsym and Rmerge. 16 years later people seem to have forgotten. I will try to dig even more ancient references… Archaeology is the name of the game.
http://www.ysbl.york.ac.uk/ccp4bb/2001/msg00383.html Cheers, Fred. From: James Foadi [mailto:james_fo...@yahoo.co.uk] Sent: Tuesday, July 11, 2017 10:03 AM To: Vellieux Frédéric <frederic.velli...@ibt.cas.cz>; CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] AW: [ccp4bb] Rmergicide Through Programming Hello Frederic. Interesting. Have you got some reference on this to share? James Dr James Foadi PhD Diamond Light Source Ltd. Diamond House Harwell Science and Innovation Campus Didcot Oxfordshire OX11 0DE United Kingdom office email: james.fo...@diamond.ac.uk<mailto:james.fo...@diamond.ac.uk> alternative email: j.fo...@imperial.ac.uk<mailto:j.fo...@imperial.ac.uk> personal web page: http://www.jfoadi.me.uk On Tuesday, 11 July 2017, 7:15, Vellieux Frédéric <frederic.velli...@ibt.cas.cz<mailto:frederic.velli...@ibt.cas.cz>> wrote: Hello, I think this needs a little bit of crystarchaeology. Rmerge and Rsym used to be different. This was at a time when data sets were typically collected from several crystals. Pre-cryo cooling, with data recorded on photographic film (Arndt-Wonacott cameras). Rmerge = agreement R-factor from data from several crystals; Rsym = agreement R-factor from symmetry-equivalents within one crystal. [I just type "agreement R-factor" in order not to have to type the formulae] At that time, people were confused about these two terms. Nowadays both are (used as) synonyms. Cheers, Fred. -----Original Message----- From: CCP4 bulletin board [mailto:CCP4BB@JISCMAIL.AC.UK<mailto:CCP4BB@JISCMAIL.AC.UK>] On Behalf Of Phil Evans Sent: Monday, July 10, 2017 5:43 PM To: CCP4BB@JISCMAIL.AC.UK<mailto:CCP4BB@JISCMAIL.AC.UK> Subject: Re: [ccp4bb] AW: [ccp4bb] Rmergicide Through Programming What is the difference between Rmerge and Rsym - I thought they were the same? Rrim == Rmeas I think Phil > On 10 Jul 2017, at 15:18, John Berrisford > <j...@ebi.ac.uk<mailto:j...@ebi.ac.uk>> wrote: > > Dear Herman > > The new PDB deposition system (OneDep) allows you to enter values for Rmerge, > Rsym, Rpim, Rrim and / or CC half. If, during deposition, you do not provide > a value for any of these metrics then we will ask you for a value for one of > them. > > Also, PDB format is a legacy format for the PDB. In 2014 mmCIF became the > archive format for the PDB and some large entries are no longer distributed > in PDB format. mmCIF is not limited by the constraints of punch cards. > > Please see > https://www.wwpdb.org/documentation/file-formats-and-the-pdb > > Regards > > John > > PDBe > > > > On 10/07/2017 09:26, > herman.schreu...@sanofi.com<mailto:herman.schreu...@sanofi.com> wrote: >> Dear All, >> >> For me this whole discussion is an example of a large number of people >> barking at the wrong tree. The real issue is not whether data processing >> programs print amongst many quality indicators an Rmerge as well, but the >> fact that the PDB and many journals still insist on using the Rmerge as >> primary quality indicator. As long as this is true, novice scientist might >> be led to believe that Rmerge is the most important quality indicator. As >> soon as the PDB and the journals request some other indicator, this will be >> over. So that is where we should direct our efforts to. >> >> I don't understand at all, why the PDB still insists on an obsolete quality >> indicator. However, the PDB format for the coordinates also dates back to >> the 1960's to be used with punch cards. >> >> My 2 cents. >> Herman >> >> >> >> -----Ursprüngliche Nachricht----- >> Von: CCP4 bulletin board >> [mailto:CCP4BB@JISCMAIL.AC.UK<mailto:CCP4BB@JISCMAIL.AC.UK>] Im Auftrag >> von Edward A. Berry >> Gesendet: Samstag, 8. Juli 2017 22:31 >> An: CCP4BB@JISCMAIL.AC.UK<mailto:CCP4BB@JISCMAIL.AC.UK> >> Betreff: Re: [ccp4bb] Rmergicide Through Programming >> >> But R-merge is not really narrower as a fraction of the mean value- it just >> gets smaller proportionantly as all the numbers get smaller: >> RMSD of .0043 for R-meas multiplied by factor of 0.022/.027 gives 0.0035 >> which is the RMSD for Rmerge. The same was true in the previous example. You >> could multiply R-meas by .5 or .2 and get a sharper distribution yet! And >> that factor would be constant, where this only applies for super-low >> redundancy. >> >> On 07/08/2017 03:23 PM, James Holton wrote: >>> The expected distribution of Rmeas values is still wider than that of >>> Rmerge for data with I/sigma=30 and average multiplicity=2.0. Graph >>> attached. >>> >>> I expect that anytime you incorporate more than one source of information >>> you run the risk of a noisier statistic because every source of information >>> can contain noise. That is, Rmeas combines information about multiplicity >>> with the absolute deviates in the data to form a statistic that is more >>> accurate that Rmerge, but also (potentially) less precise. >>> >>> Perhaps that is what we are debating here? Which is better? accuracy or >>> precision? Personally, I prefer to know both. >>> >>> -James Holton >>> MAD Scientist >>> >>> On 7/8/2017 11:02 AM, Frank von Delft wrote: >>>> It is quite easy to end up with low multiplicities in the low resolution >>>> shell, especially for low symmetry and fast-decaying crystals. >>>> >>>> It is this scenario where Rmerge (lowres) is more misleading than Reas. >>>> >>>> phx >>>> >>>> >>>> On 08/07/2017 17:31, James Holton wrote: >>>>> What does Rmeas tell us that Rmerge doesn't? Given that we know the >>>>> multiplicity? >>>>> >>>>> -James Holton >>>>> MAD Scientist >>>>> >>>>> On 7/8/2017 9:15 AM, Frank von Delft wrote: >>>>>> Anyway, back to reality: does anybody still use R statistics to >>>>>> evaluate anything other than /strong/ data? Certainly I never look at >>>>>> it except for the low-resolution bin (or strongest reflections). >>>>>> Specifically, a "2%-dataset" in that bin is probably healthy, while a >>>>>> "9%-dataset" probably Has Issues. >>>>>> >>>>>> In which case, back to Jacob's question: what does Rmerge tell us that >>>>>> Rmeas doesn't. >>>>>> >>>>>> phx >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> On 08/07/2017 17:02, James Holton wrote: >>>>>>> Sorry for the confusion. I was going for brevity! And failed. >>>>>>> >>>>>>> I know that the multiplicity correction is applied on a per-hkl basis >>>>>>> in the calculation of Rmeas. However, the average multiplicity over >>>>>>> the whole calculation is most likely not an integer. Some hkls may be >>>>>>> observed twice while others only once, or perhaps 3-4 times in the same >>>>>>> scaling run. >>>>>>> >>>>>>> Allow me to do the error propagation properly. Consider the scenario: >>>>>>> >>>>>>> Your outer resolution bin has a true I/sigma = 1.00 and average >>>>>>> multiplicity of 2.0. Let's say there are 100 hkl indices in this bin. >>>>>>> I choose the "true" intensities of each hkl from an exponential (aka >>>>>>> Wilson) distribution. Further assume the background is high, so the >>>>>>> error in each observation after background subtraction may be taken >>>>>>> from a Gaussian distribution. Let's further choose the per-hkl >>>>>>> multiplicity from a Poisson distribution with expectation value 2.0, so >>>>>>> 0 is possible, but the long-term average multiplicity is 2.0. For R >>>>>>> calculation, when multiplicity of any given hkl is less than 2 it is >>>>>>> skipped. What I end up with after 120,000 trials is a distribution of >>>>>>> values for each R factor. See attached graph. >>>>>>> >>>>>>> What I hope is readily apparent is that the distribution of >>>>>>> Rmerge values is taller and sharper than that of the Rmeas values. The >>>>>>> most likely Rmeas is 80% and that of Rmerge is 64.6%. This is >>>>>>> expected, of course. But what I hope to impress upon you is that the >>>>>>> most likely value is not generally the one that you will get! The >>>>>>> distribution has a width. Specifically, Rmeas could be as low as 40%, >>>>>>> or as high as 209%, depending on the trial. Half of the trial results >>>>>>> falling between 71.4% and 90.3%, a range of 19 percentage points. >>>>>>> Rmerge has a middle-half range from 57.6% to 72.9% (15.3 percentage >>>>>>> points). This range of possible values of Rmerge or Rmeas from data >>>>>>> with the same intrinsic quality is what I mean when I say "numerical >>>>>>> instability". Each and every trial had the same true I/sigma and >>>>>>> multiplicity, and yet the R factors I get vary depending on the trial. >>>>>>> Unfortunately for most of us with real data, you only ever get one >>>>>>> trial, and you can't predict which Rmeas or Rmerge you'll get. >>>>>>> >>>>>>> My point here is that R statistics in general are not comparable from >>>>>>> experiment to experiment when you are looking at data with low average >>>>>>> intensity and low multiplicity, and it appears that Rmeas is less >>>>>>> stable than Rmerge. Not by much, mind you, but still jumps around more. >>>>>>> >>>>>>> Hope that is clearer? >>>>>>> >>>>>>> Note that in no way am I suggesting that low-multiplicity is the right >>>>>>> way to collect data. Far from it. Especially with modern detectors >>>>>>> that have negligible read-out noise. But when micro crystals only give >>>>>>> off a handful of photons each before they die, low multiplicity might >>>>>>> be all you have. >>>>>>> >>>>>>> -James Holton >>>>>>> MAD Scientist >>>>>>> >>>>>>> >>>>>>> >>>>>>> On 7/7/2017 2:33 PM, Edward A. Berry wrote: >>>>>>>> I think the confusion here is that the "multiplicity correction" >>>>>>>> is applied on each reflection, where it will be an integer 2 or >>>>>>>> greater (can't estimate variance with only one measurement). >>>>>>>> You can only correct in an approximate way using using the >>>>>>>> average multiplicity of the dataset, since it would depend on the >>>>>>>> distribution of multiplicity over the reflections. >>>>>>>> >>>>>>>> And the correction is for r-merge. You don't need to apply a >>>>>>>> correction to R-meas. >>>>>>>> R-meas is a redundancy-independent best estimate of the variance. >>>>>>>> Whatever you would have used R-merge for (hopefully taking >>>>>>>> allowance for the multiplicity) you can use R-meas and not worry about >>>>>>>> multiplicity. >>>>>>>> Again, what information does R-merge provide that R-meas does >>>>>>>> not provide in a more accurate way? >>>>>>>> >>>>>>>> According to the denso manual, one way to artificially reduce >>>>>>>> R-merge is to include reflections with only one measure >>>>>>>> (averaging in a lot of zero's always helps bring an average >>>>>>>> down), and they say there were actually some programs that did >>>>>>>> that. However I'm quite sure none of the ones we rely on today do that. >>>>>>>> >>>>>>>> On 07/07/2017 03:12 PM, Kay Diederichs wrote: >>>>>>>>> James, >>>>>>>>> >>>>>>>>> I cannot follow you. "n approaches 1" can only mean n = 2 because n >>>>>>>>> is integer. And for n=2 the sqrt(n/(n-1)) factor is well-defined. For >>>>>>>>> n=1, neither contributions to Rmeas nor Rmerge nor to any other >>>>>>>>> precision indicator can be calculated anyway, because there's nothing >>>>>>>>> this measurement can be compared against. >>>>>>>>> >>>>>>>>> just my 2 cents, >>>>>>>>> >>>>>>>>> Kay >>>>>>>>> >>>>>>>>> On Fri, 7 Jul 2017 10:57:17 -0700, James Holton >>>>>>>>> <jmhol...@slac.stanford.edu<mailto:jmhol...@slac.stanford.edu>> wrote: >>>>>>>>> >>>>>>>>>> I happen to be one of those people who think Rmerge is a very >>>>>>>>>> useful statistic. Not as a method of evaluating the >>>>>>>>>> resolution limit, which is mathematically ridiculous, but for >>>>>>>>>> a host of other important things, like evaluating the >>>>>>>>>> performance of data collection equipment, and evaluating the >>>>>>>>>> isomorphism of different crystals, to name a few. >>>>>>>>>> >>>>>>>>>> I like Rmerge because it is a simple statistic that has a >>>>>>>>>> simple formula and has not undergone any "corrections". >>>>>>>>>> Corrections increase complexity, and complexity opens the >>>>>>>>>> door to manipulation by the desperate and/or misguided. For >>>>>>>>>> example, overzealous outlier rejection is a common way to >>>>>>>>>> abuse R factors, and it is far too often swept under the rug, >>>>>>>>>> sometimes without the user even knowing about it. This is >>>>>>>>>> especially problematic when working in a regime where the statistic >>>>>>>>>> of interest is unstable, and for R factors this is low intensity >>>>>>>>>> data. >>>>>>>>>> Rejecting just the right "outliers" can make any R factor >>>>>>>>>> look a lot better. Why would Rmeas be any more unstable than >>>>>>>>>> Rmerge? Look at the formula. There is an "n-1" in the >>>>>>>>>> denominator, where n is the multiplicity. So, what happens >>>>>>>>>> when n approaches 1 ? What happens when n=1? This is not to >>>>>>>>>> say Rmerge is better than Rmeas. In fact, I believe the >>>>>>>>>> latter is generally superior to the first, unless you are >>>>>>>>>> working near n = 1. The sqrt(n/(n-1)) is trying to correct >>>>>>>>>> for bias in the R statistic, but fighting one infinity with another >>>>>>>>>> infinity is a dangerous game. >>>>>>>>>> >>>>>>>>>> My point is that neither Rmerge nor Rmeas are easily >>>>>>>>>> interpreted without knowing the multiplicity. If you see >>>>>>>>>> Rmeas = 10% and the multiplicity is 10, then you know what >>>>>>>>>> that means. Same for Rmerge, since at n=10 both stats have >>>>>>>>>> nearly the same value. But if you have Rmeas = 45% and >>>>>>>>>> multiplicity = 1.05, what does that mean? Rmeas will be only >>>>>>>>>> 33% if the multiplicity is rounded up to 1.1. This is what I >>>>>>>>>> mean by "numerical instability", the value of the R statistic >>>>>>>>>> itself becomes sensitive to small amounts of noise, and >>>>>>>>>> behaves more and more like a random number generator. And if >>>>>>>>>> you have Rmeas = 33% and no indication of multiplicity, it is >>>>>>>>>> hard to know what is going on. I personally am a lot more >>>>>>>>>> comfortable seeing qualitative agreement between Rmerge and Rmeas, >>>>>>>>>> because that means the numerical instability of the multiplicity >>>>>>>>>> correction didn't mess anything up. >>>>>>>>>> >>>>>>>>>> Of course, when the intensity is weak R statistics in general >>>>>>>>>> are not useful. Both Rmeas and Rmerge have the sum of all >>>>>>>>>> intensities in the denominator, so when the bin-wide sum >>>>>>>>>> approaches zero you have another infinity to contend with. >>>>>>>>>> This one starts to rear its ugly head once I/sigma drops >>>>>>>>>> below about 3, and this is why our ancestors always applied a >>>>>>>>>> sigma cutoff before computing an R factor. Our small-molecule >>>>>>>>>> colleagues still do this! They call it "R1". And it is an >>>>>>>>>> excellent indicator of the overall relative error. The >>>>>>>>>> relative error in the outermost bin is not meaningful, and strangely >>>>>>>>>> enough nobody ever reported the outer-resolution Rmerge before 1995. >>>>>>>>>> >>>>>>>>>> For weak signals, Correlation Coefficients are better, but >>>>>>>>>> for strong signals CC pegs out at >95%, making it harder to see >>>>>>>>>> relative errors. >>>>>>>>>> I/sigma is what we'd like to know, but the value of "sigma" >>>>>>>>>> is still prone to manipulation by not just outlier rejection, >>>>>>>>>> but massaging the so-called "error model". Suffice it to >>>>>>>>>> say, crystallographic data contain more than one type of error. >>>>>>>>>> Some sources are important for weak spots, others are >>>>>>>>>> important for strong spots, and still others are only >>>>>>>>>> apparent in the mid-range. Some sources of error are only >>>>>>>>>> important at low multiplicity, and others only manifest at high >>>>>>>>>> multiplicity. >>>>>>>>>> There is no single number that can be used to evaluate all aspects >>>>>>>>>> of data quality. >>>>>>>>>> >>>>>>>>>> So, I remain a champion of reporting Rmerge. Not in the >>>>>>>>>> high-angle bin, because that is essentially a random number, >>>>>>>>>> but overall Rmerge and low-angle-bin Rmerge next to >>>>>>>>>> multiplicity, Rmeas, CC1/2 and other statistics is the only >>>>>>>>>> way you can glean enough information about where the errors >>>>>>>>>> are coming from in the data. Rmeas is a useful addition >>>>>>>>>> because it helps us correct for multiplicity without having >>>>>>>>>> to do math in our head. Users generally thank you for that. >>>>>>>>>> Rmerge, however, has served us well for more than half a >>>>>>>>>> century, and I believe Uli Arndt knew what he was doing. I >>>>>>>>>> hope we all know enough about history to realize that future >>>>>>>>>> generations seldom thank their ancestors for "protecting" them from >>>>>>>>>> information. >>>>>>>>>> >>>>>>>>>> -James Holton >>>>>>>>>> MAD Scientist >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> On 7/5/2017 10:36 AM, Graeme Winter wrote: >>>>>>>>>>> Frank, >>>>>>>>>>> >>>>>>>>>>> you are asking me to remove features that I like, so I would feel >>>>>>>>>>> that the challenge is for you to prove that this is harmful however: >>>>>>>>>>> >>>>>>>>>>> - at the minimum, I find it a useful check sum that the stats >>>>>>>>>>> are internally consistent (though I interpret it for lots of other >>>>>>>>>>> reasons too) >>>>>>>>>>> - it is faulty I agree, but (with caveats) still useful >>>>>>>>>>> IMHO >>>>>>>>>>> >>>>>>>>>>> Sorry for being terse, but I remain to be convinced that >>>>>>>>>>> removing it increases the amount of information >>>>>>>>>>> >>>>>>>>>>> CC’ing BB as requested >>>>>>>>>>> >>>>>>>>>>> Best wishes Graeme >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>>> On 5 Jul 2017, at 17:17, Frank von Delft >>>>>>>>>>>> <frank.vonde...@sgc.ox.ac.uk<mailto:frank.vonde...@sgc.ox.ac.uk>> >>>>>>>>>>>> wrote: >>>>>>>>>>>> >>>>>>>>>>>> You keep not answering the challenge. >>>>>>>>>>>> >>>>>>>>>>>> It's really simple: what information does Rmerge provide that >>>>>>>>>>>> Rmeas doesn't. >>>>>>>>>>>> >>>>>>>>>>>> (If you answer, email to the BB.) >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On 05/07/2017 16:04, >>>>>>>>>>>> graeme.win...@diamond.ac.uk<mailto:graeme.win...@diamond.ac.uk> >>>>>>>>>>>> wrote: >>>>>>>>>>>>> Dear Frank, >>>>>>>>>>>>> >>>>>>>>>>>>> You are forcefully arguing essentially that others are wrong if >>>>>>>>>>>>> we feel an existing statistic continues to be useful, and instead >>>>>>>>>>>>> insist that it be outlawed so that we may not make use of it, >>>>>>>>>>>>> just in case someone misinterprets it. >>>>>>>>>>>>> >>>>>>>>>>>>> Very well >>>>>>>>>>>>> >>>>>>>>>>>>> I do however express disquiet that we as software developers feel >>>>>>>>>>>>> browbeaten to remove the output we find useful because “the >>>>>>>>>>>>> community” feel that it is obsolete. >>>>>>>>>>>>> >>>>>>>>>>>>> I feel that Jacob’s short story on this thread illustrates that >>>>>>>>>>>>> educating the next generation of crystallographers to understand >>>>>>>>>>>>> what all of the numbers mean is critical, and that a >>>>>>>>>>>>> numerological approach of trying to optimise any one statistic is >>>>>>>>>>>>> essentially doomed. Precisely the same argument could be made for >>>>>>>>>>>>> people cutting the “resolution” at the wrong place in order to >>>>>>>>>>>>> improve the average I/sig(I) of the data set. >>>>>>>>>>>>> >>>>>>>>>>>>> Denying access to information is not a solution to >>>>>>>>>>>>> misinterpretation, from where I am sat, however I acknowledge >>>>>>>>>>>>> that other points of view exist. >>>>>>>>>>>>> >>>>>>>>>>>>> Best wishes Graeme >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On 5 Jul 2017, at 12:11, Frank von Delft >>>>>>>>>>>>> <frank.vonde...@sgc.ox.ac.uk<mailto:frank.vonde...@sgc.ox.ac.uk><mailto:frank.vonde...@sgc.ox.ac.uk<mailto:frank.vonde...@sgc.ox.ac.uk>>> >>>>>>>>>>>>> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> Graeme, Andrew >>>>>>>>>>>>> >>>>>>>>>>>>> Jacob is not arguing against an R-based statistic; he's pointing >>>>>>>>>>>>> out that leaving out the multiplicity-weighting is prehistoric >>>>>>>>>>>>> (Diederichs & Karplus published it 20 years ago!). >>>>>>>>>>>>> >>>>>>>>>>>>> So indeed: Rmerge, Rpim and I/sigI give different information. >>>>>>>>>>>>> As you say. >>>>>>>>>>>>> >>>>>>>>>>>>> But no: Rmerge and Rmeas and Rcryst do NOT give different >>>>>>>>>>>>> information. Except: >>>>>>>>>>>>> >>>>>>>>>>>>> * Rmerge is a (potentially) misleading version of Rmeas. >>>>>>>>>>>>> >>>>>>>>>>>>> * Rcryst and Rmerge and Rsym are terms that no longer have >>>>>>>>>>>>> significance in the single cryo-dataset world. >>>>>>>>>>>>> >>>>>>>>>>>>> phx. >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On 05/07/2017 09:43, Andrew Leslie wrote: >>>>>>>>>>>>> >>>>>>>>>>>>> I would like to support Graeme in his wish to retain Rmerge in >>>>>>>>>>>>> Table 1, essentially for exactly the same reasons. >>>>>>>>>>>>> >>>>>>>>>>>>> I also strongly support Francis Reyes comment about the >>>>>>>>>>>>> usefulness of Rmerge at low resolution, and I would add to his >>>>>>>>>>>>> list that it can also, in some circumstances, be more indicative >>>>>>>>>>>>> of the wrong choice of symmetry (too high) than the statistics >>>>>>>>>>>>> that come from POINTLESS (excellent though that program is!). >>>>>>>>>>>>> >>>>>>>>>>>>> Andrew >>>>>>>>>>>>> On 5 Jul 2017, at 05:44, Graeme Winter >>>>>>>>>>>>> <graeme.win...@gmail.com<mailto:graeme.win...@gmail.com><mailto:graeme.win...@gmail.com<mailto:graeme.win...@gmail.com>>> >>>>>>>>>>>>> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>> HI Jacob >>>>>>>>>>>>> >>>>>>>>>>>>> Yes, I got this - and I appreciate the benefit of Rmeas for >>>>>>>>>>>>> dealing with measuring agreement for small-multiplicity >>>>>>>>>>>>> observations. Having this *as well* is very useful and I agree >>>>>>>>>>>>> Rmeas / Rpim / CC-half should be the primary “quality” statistics. >>>>>>>>>>>>> >>>>>>>>>>>>> However, you asked if there is any reason to *keep* rather >>>>>>>>>>>>> than *eliminate* Rmerge, and I offered one :o) >>>>>>>>>>>>> >>>>>>>>>>>>> I do not see what harm there is reporting Rmerge, even if it is >>>>>>>>>>>>> just used in the inner shell or just used to capture a flavour of >>>>>>>>>>>>> the data set overall. I also appreciate that Rmeas converges to >>>>>>>>>>>>> the same value for large multiplicity i.e.: >>>>>>>>>>>>> >>>>>>>>>>>>> Overall InnerShell OuterShell >>>>>>>>>>>>> Low resolution limit 39.02 39.02 1.39 >>>>>>>>>>>>> High resolution limit 1.35 6.04 1.35 >>>>>>>>>>>>> >>>>>>>>>>>>> Rmerge (within I+/I-) 0.080 0.057 2.871 >>>>>>>>>>>>> Rmerge (all I+ and I-) 0.081 0.059 2.922 >>>>>>>>>>>>> Rmeas (within I+/I-) 0.081 0.058 2.940 >>>>>>>>>>>>> Rmeas (all I+ & I-) 0.082 0.059 2.958 >>>>>>>>>>>>> Rpim (within I+/I-) 0.013 0.009 0.628 >>>>>>>>>>>>> Rpim (all I+ & I-) 0.009 0.007 0.453 >>>>>>>>>>>>> Rmerge in top intensity bin 0.050 - - >>>>>>>>>>>>> Total number of observations 1265512 16212 53490 >>>>>>>>>>>>> Total number unique 17515 224 1280 >>>>>>>>>>>>> Mean((I)/sd(I)) 29.7 104.3 1.5 >>>>>>>>>>>>> Mn(I) half-set correlation CC(1/2) 1.000 1.000 0.778 >>>>>>>>>>>>> Completeness 100.0 99.7 100.0 >>>>>>>>>>>>> Multiplicity 72.3 72.4 41.8 >>>>>>>>>>>>> >>>>>>>>>>>>> Anomalous completeness 100.0 100.0 100.0 >>>>>>>>>>>>> Anomalous multiplicity 37.2 42.7 21.0 >>>>>>>>>>>>> DelAnom correlation between half-sets 0.497 0.766 -0.026 >>>>>>>>>>>>> Mid-Slope of Anom Normal Probability 1.039 - - >>>>>>>>>>>>> >>>>>>>>>>>>> (this is a good case for Rpim & CC-half as resolution >>>>>>>>>>>>> limit >>>>>>>>>>>>> criteria) >>>>>>>>>>>>> >>>>>>>>>>>>> If the statistics you want to use are there & some others >>>>>>>>>>>>> also, what is the pressure to remove them? Surely we want >>>>>>>>>>>>> to educate on how best to interpret the entire table above >>>>>>>>>>>>> to get a fuller picture of the overall quality of the >>>>>>>>>>>>> data? My 0th-order request would be to publish the three >>>>>>>>>>>>> shells as above ;o) >>>>>>>>>>>>> >>>>>>>>>>>>> Cheers Graeme >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On 4 Jul 2017, at 22:09, Keller, Jacob >>>>>>>>>>>>> <kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org><mailto:kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org>>> >>>>>>>>>>>>> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>> I suggested replacing Rmerge/sym/cryst with Rmeas, not Rpim. >>>>>>>>>>>>> Rmeas is simply (Rmerge * sqrt(n/n-1)) where n is the number of >>>>>>>>>>>>> measurements of that reflection. It's merely a way of correcting >>>>>>>>>>>>> for the multiplicity-related artifact of Rmerge, which is >>>>>>>>>>>>> becoming even more of a problem with data sets of increasing >>>>>>>>>>>>> variability in multiplicity. Consider the case of comparing a >>>>>>>>>>>>> data set with a multiplicity of 2 versus one of 100: equivalent >>>>>>>>>>>>> data quality would yield Rmerges diverging by a factor of ~1.4. >>>>>>>>>>>>> But this has all been covered before in several papers. It can be >>>>>>>>>>>>> and is reported in resolution bins, so can used exactly as you >>>>>>>>>>>>> say. So, why not "disappear" Rmerge from the software? >>>>>>>>>>>>> >>>>>>>>>>>>> The only reason I could come up with for keeping it is historical >>>>>>>>>>>>> reasons or comparisons to previous datasets, but anyway those >>>>>>>>>>>>> comparisons would be confounded by variabities in multiplicity >>>>>>>>>>>>> and a hundred other things, so come on, developers, just comment >>>>>>>>>>>>> it out! >>>>>>>>>>>>> >>>>>>>>>>>>> JPK >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> -----Original Message----- >>>>>>>>>>>>> From: >>>>>>>>>>>>> graeme.win...@diamond.ac.uk<mailto:graeme.win...@diamond.ac.uk><mailto:graeme.win...@diamond.ac.<mailto:graeme.win...@diamond.ac.> >>>>>>>>>>>>> uk> >>>>>>>>>>>>> [mailto:graeme.win...@diamond.ac.uk<mailto:graeme.win...@diamond.ac.uk>] >>>>>>>>>>>>> Sent: Tuesday, July 04, 2017 4:37 PM >>>>>>>>>>>>> To: Keller, Jacob >>>>>>>>>>>>> <kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org><mailto:kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org>> >>>>>>>>>>>>> > >>>>>>>>>>>>> Cc: >>>>>>>>>>>>> ccp4bb@jiscmail.ac.uk<mailto:ccp4bb@jiscmail.ac.uk><mailto:ccp4bb@jiscmail.ac.uk<mailto:ccp4bb@jiscmail.ac.uk>> >>>>>>>>>>>>> Subject: Re: [ccp4bb] Rmergicide Through Programming >>>>>>>>>>>>> >>>>>>>>>>>>> HI Jacob >>>>>>>>>>>>> >>>>>>>>>>>>> Unbiased estimate of the true unmerged I/sig(I) of your >>>>>>>>>>>>> data (I find this particularly useful at low resolution) >>>>>>>>>>>>> i.e. if your inner shell Rmerge is 10% your data agree >>>>>>>>>>>>> very poorly; if 2% says your data agree very well provided >>>>>>>>>>>>> you have sensible multiplicity… obviously depends on >>>>>>>>>>>>> sensible interpretation. Rpim hides this (though tells you >>>>>>>>>>>>> more about the quality of average measurement) >>>>>>>>>>>>> >>>>>>>>>>>>> Essentially, for I/sig(I) you can (by and large) adjust your >>>>>>>>>>>>> sig(I) values however you like if you were so inclined. You can >>>>>>>>>>>>> only adjust Rmerge by excluding measurements. >>>>>>>>>>>>> >>>>>>>>>>>>> I would therefore defend that - amongst the other stats >>>>>>>>>>>>> you enumerate below - it still has a place >>>>>>>>>>>>> >>>>>>>>>>>>> Cheers Graeme >>>>>>>>>>>>> >>>>>>>>>>>>> On 4 Jul 2017, at 14:10, Keller, Jacob >>>>>>>>>>>>> <kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org><mailto:kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org>>> >>>>>>>>>>>>> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>> Rmerge does contain information which complements the others. >>>>>>>>>>>>> >>>>>>>>>>>>> What information? I was trying to think of a counterargument to >>>>>>>>>>>>> what I proposed, but could not think of a reason in the world to >>>>>>>>>>>>> keep reporting it. >>>>>>>>>>>>> >>>>>>>>>>>>> JPK >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On 4 Jul 2017, at 12:00, Keller, Jacob >>>>>>>>>>>>> <kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org><mailto:kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org>><mailto:kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org>>> >>>>>>>>>>>>> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>> Dear Crystallographers, >>>>>>>>>>>>> >>>>>>>>>>>>> Having been repeatedly chagrinned about the continued use and >>>>>>>>>>>>> reporting of Rmerge rather than Rmeas or similar, I thought of a >>>>>>>>>>>>> potential way to promote the change: what if merging programs >>>>>>>>>>>>> would completely omit Rmerge/cryst/sym? Is there some reason to >>>>>>>>>>>>> continue to report these stats, or are they just grandfathered >>>>>>>>>>>>> into the software? I doubt that any journal or crystallographer >>>>>>>>>>>>> would insist on reporting Rmerge per se. So, I wonder what >>>>>>>>>>>>> developers would think about commenting out a few lines of their >>>>>>>>>>>>> code, seeing what happens? Maybe a comment to the effect of >>>>>>>>>>>>> "Rmerge is now deprecated; use Rmeas" would be useful as well. >>>>>>>>>>>>> Would something catastrophic happen? >>>>>>>>>>>>> >>>>>>>>>>>>> All the best, >>>>>>>>>>>>> >>>>>>>>>>>>> Jacob Keller >>>>>>>>>>>>> >>>>>>>>>>>>> ******************************************* >>>>>>>>>>>>> Jacob Pearson Keller, PhD >>>>>>>>>>>>> Research Scientist >>>>>>>>>>>>> HHMI Janelia Research Campus / Looger lab >>>>>>>>>>>>> Phone: (571)209-4000 x3159 >>>>>>>>>>>>> Email: >>>>>>>>>>>>> kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org><mailto:kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org>>< >>>>>>>>>>>>> ma ilto:kell...@janelia.hhmi.org<mailto:kell...@janelia.hhmi.org>> >>>>>>>>>>>>> ******************************************* >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> -- >>>>>>>>>>>>> This e-mail and any attachments may contain confidential, >>>>>>>>>>>>> copyright and or privileged material, and are for the use of the >>>>>>>>>>>>> intended addressee only. If you are not the intended addressee or >>>>>>>>>>>>> an authorised recipient of the addressee please notify us of >>>>>>>>>>>>> receipt by returning the e-mail and do not use, copy, retain, >>>>>>>>>>>>> distribute or disclose the information in or attached to the >>>>>>>>>>>>> e-mail. >>>>>>>>>>>>> Any opinions expressed within this e-mail are those of the >>>>>>>>>>>>> individual and not necessarily of Diamond Light Source Ltd. >>>>>>>>>>>>> Diamond Light Source Ltd. cannot guarantee that this e-mail or >>>>>>>>>>>>> any attachments are free from viruses and we cannot accept >>>>>>>>>>>>> liability for any damage which you may sustain as a result of >>>>>>>>>>>>> software viruses which may be transmitted in or with the message. >>>>>>>>>>>>> Diamond Light Source Limited (company no. 4375679). >>>>>>>>>>>>> Registered in England and Wales with its registered office >>>>>>>>>>>>> at Diamond House, Harwell Science and Innovation Campus, >>>>>>>>>>>>> Didcot, Oxfordshire, OX11 0DE, United Kingdom >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> > > -- > John Berrisford > PDBe > European Bioinformatics Institute (EMBL-EBI) European Molecular > Biology Laboratory Wellcome Trust Genome Campus Hinxton Cambridge CB10 > 1SD UK > Tel: +44 1223 492529 > > http://www.pdbe.org<http://www.pdbe.org/> > http://www.facebook.com/proteindatabank > http://twitter.com/PDBeurope ----- Upozornění: Není-li v této zprávě výslovně uvedeno jinak, má tato E-mailová zpráva nebo její přílohy pouze informativní charakter. 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