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Dear Jesus, Be careful that the number of particles jumping between classes is very much dependent on orientation sampling. If your sampling is too coarse, particles will not be able to find their correct assignement. If you make your sampling finer and finer, you will see less and less particles jumping between classes. Just be careful that then, particles may be artificially stuck in a particular class. Sjors’s group suggests not going much finer than the orientation accuracy. An analysis of particle behavior should definitely be in that range to be meaningful. Hope this helps, Amedee -- Amedee des Georges, Ph.D. Assistant Professor, Structural Biology Initiative, CUNY Advanced Science Research Center Assistant professor of Chemistry & Biochemistry, City College of New York [log in to unmask] <mailto:[log in to unmask]> - http://asrc.cuny.edu <http://asrc.cuny.edu/> - 212-413-3232 > On Jun 2, 2016, at 5:26 AM, Jesus GOMEZ <[log in to unmask]> wrote: > > Thank you both for the fast responses, > > Grigory, that is a really interesting paper. It does analyse the same phenomena I'm interested in, but their focus is in localizing particles that belong to the same class and have been separated, while my focus is to find particles that belong nowhere and have been aimlessly shifting classes. Anyway, their approach to merging classes seems quite useful. As you say, particles may jump between similar classes, and currently I try to take this into account by giving a intermediate score to those particles that travel frequently between the same few classes, but actually merging the classes might be a better approach. I believe I will either try to mimic their scrip in bash and add it to mine (with a proper authorship mention) or ask our IT team whether it would be possible to get matlab installed in my computer. > > Reza, you are right about Sparx, is a quite versatile software. Sadly, our cluster seems to not like it so much, and we have some serious problems running some of the programs included, mainly when using MPI. I'm running a small test, but this far sxisac seems to run only using one cpu, so I expect it will take quite long to finish. Our IT team is working on this, but currently is not possible for me to use it efficiently. Still, knowing that this program does this is helpful, I can go into the files and related papers and try to find the criteria they use. > > Thanks again for your helpful comments, > > Best regards, > > Jesus > > > > > On 2016-06-01 14:10, Reza Khayat wrote: >> Hi, >> >> ISAC does what you’re seeking and a lot more. It’s in the Sparx >> package. >> >> Best wishes, >> Reza >> >> Reza Khayat, PhD >> >> Assistant Professor >> >> Department of Chemistry >> >> City College of New York >> >> 85 Saint Nicholas Terrace, CDI 2.318 >> >> New York, NY 10031 >> >> http://www.khayatlab.org/ <http://www.khayatlab.org/> [1] >> >> 212-650-6070 >> >> FROM: Collaborative Computational Project in Electron cryo-Microscopy >> [mailto:[log in to unmask] <mailto:[log in to unmask]>] ON BEHALF OF Grigory Sharov >> SENT: Wednesday, June 01, 2016 7:58 AM >> TO: [log in to unmask] <mailto:[log in to unmask]> >> SUBJECT: Re: [ccpem] Stability of particles in Relion classifications >> >> >> Hi Jesus, >> >> you might look into this [2] paper from Frank's group. The matlab >> script described there should work (after few modifications) for the >> latest Relion version. >> >> Another thing is that particles will keep jumping if classes are very >> similar. You could look into ccpem archives about discussion on 3D >> classification convergence. >> >> Best regards, >> Grigory >> >> -------------------------------------------------------------------------------- >> >> >> Grigory Sharov, Ph.D. >> >> Institute of Genetics and Molecular and Cellular Biology >> Integrated Structural Biology Department (CBI) >> 1, rue Laurent Fries >> 67404 Illkirch, France >> >> tel. 03 69 48 51 00 >> >> e-mail: [log in to unmask] <mailto:[log in to unmask]> [3] >> >> On Wed, Jun 1, 2016 at 1:34 PM, Jesus GOMEZ <[log in to unmask] <mailto:[log in to unmask]> [4]> >> wrote: >> >>> Dear all, >>> >>> Currently I'm working with Relion and I find myself in the >>> following situation: In each iteration there is a percentage (around >>> 10-15% in the later iterations) of particles that changes classes. >>> What I don't know is if these particles are the same for all the >>> iterations or change every round of classification. >>> >>> To address this my idea is to classify my particles based on their >>> stability along the 2D or 3D classification, meaning that those >>> particles that change classes few times will be considered good, and >>> those changing many times will be considered bad and removed from >>> the dataset. Note that this is different from the "particle sorting" >>> option in Relion, which only takes into account the correlation >>> between each particle and the class it belongs to for one given >>> iteration (my idea is to combine these two types of classification >>> for a more complete cleaning of the dataset). This is not very >>> difficult technically, since the data needed is in the *data.star >>> files outputted by Relion. In fact I have written a very simple bash >>> application that reads the data and awards points to the particles >>> based on events such as "staying in the same class", "times stayed >>> in the same class in a row" and such, placing more weight in the >>> later iterations, which are more relevant in my opinion. >>> >>> My question is: does anyone use or know about something similar? >>> I'm looking for a solution for Relion, but any other program that >>> does this would also be welcome. Since I'm not a expert in this and >>> I'm using a quite simple and arbitrary approach to scoring the >>> particles I feel like there might already be a more established >>> solution for my problem that I have overlooked. >>> >>> Thank you in advance, >>> >>> Jesus Gomez de Segura >> >> >> >> Links: >> ------ >> [1] http://www.khayatlab.org/ <http://www.khayatlab.org/> >> [2] http://embl.fr/%20http:/dx.doi.org/10.1016/j.jsb.2014.10.006 <http://embl.fr/%20http:/dx.doi.org/10.1016/j.jsb.2014.10.006> >> [3] mailto:[log in to unmask] <mailto:[log in to unmask]> >> [4] mailto:[log in to unmask] <mailto:[log in to unmask]>