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| == Wednesday March 16, 2011 - P.M. Practical EMAN2 SPT tutorial == SPT (single particle tomography) capabilities are relatively new in EMAN2. They were inspired by Michael Schmid's studies on sub-volume averaging (mostly on viruses), and a stubborn student's insistence on doing extensive sub-volume averaging on chaperons. |
== Wednesday - P.M. == |
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| This session will cover the beta version of a small fraction of the possibilities for SPT processing EMAN2 will eventually offer. | This session will cover the new tools for single particle tomography in EMAN2. Unfortunately, this technique is very memory-intensive and compute-intensive. The 3 gb of ram available on the workshop computers is barely sufficient to do some small examples, and full 3-D alignments of large sets of particles can take many hours of computation. |
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| == OUTLINE == * 1) SPT processing through EMAN2's workflow (e2workflow.py) * 2) Sub-volume extraction from tomograms using EMAN2's 3D particle picking tool (e2tomoboxer.py) * 3) "Preparation" of extracted particles for alignment. [Details later. /!\ For a myriad of reasons, it is NOT recommendable to align and average sub-volumes directly after extraction without "preparing" them first]. * 4) Reference-based alignment and averaging. <!> ''PLEASE NOTE that "particle" and "sub-volume" are used interchangeably'' |
So, for purposes of the tutorial, we will learn how to use the particle picker, and do a couple of small examples which can be completed in the available time. |
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| == SOFTWARE == All necessary software is provided as part of EMAN2. If you don't have EMAN2 installed, you can download the most updated version (for your specific platform, Windows, Linux or Mac), from here: [[http://ncmi.bcm.edu/ncmi/software/counter_222/software_86]] |
== DATA == [[attachment:e2spt_data.zip| e2spt_data.zip|&do=get]] |
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| == RAW DATA == We have prepared sample data for this tutorial. The tomogram in the link below comes from a tilt series of epsilon15 virus particles ''in vitro'', recorded using Zernike phase-plate technology: |
== TUTORIAL DOCUMENT == Not available here for now. Get it through this site: |
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| [[attachment:e15phaseplate.rec]] | http://blake.bcm.edu/emanwiki/Ws2011/Agenda |
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| The following tomogram also comes from a tilt series of epsilon15 viruses ''in vitro'' but was recorded under conventional cryoEM imaging conditions: | == Monstrous command for alignment with e2classaverage3d.py == |
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| [[attachment:e15normal.rec]] | e2classaverage3d.py --input=e15pp_set1_stack.hdf --output=e15pp_set1_aligned.hdf --ref=e15ref_prep_icos_bin2.hdf --npeakstorefine=1 -v 3 --mask=mask.sharp:outer_radius=48 --preprocess=filter.lowpass.gauss:cutoff_freq=.02 --align=rotate_translate_3d:search=10:delta=8:dphi=8:verbose=1:sym=icos --parallel=thread:2 --ralign=refine_3d_grid:delta=3:range=9:search=2 --averager=mean.tomo --aligncmp=ccc.tomo --raligncmp=ccc.tomo --shrink=3 --shrinkrefine=3 --savesteps --saveali --iter=8 --normproc=normalize --sym=c1 --keep=0.8 --path=whatever_folder_I_want |
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| == BOXING == There are two options for opening the tomogram for purposes of boxing it. |
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| 1) Directly, by typing e2tomoboxer.py followed my the path to the tomogram file at the commandline. | |
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| 2) Or you can launch e2workflow.py from the commandline and access a tomogram through the browser in the tomographic menu. | == Monstrous command for alignment with e2tomoallvsall.py == |
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| [In theory, you can open a tomogram for contemplation purposes by typing: "e2display.py <my_tomogram_path_name_goes_here>" at the commandline. /!\ This is NOT recommendable, unless you have a grossly large (VERY, VERY large) amount of virtual memory on your computer; otherwise, catastrophe WILL befall upon you]. |
e2tomoallvsall.py -v 1 --path=AVSAs087 --input=CENTEREDvsD8aliVSapo_s087.hdf --shrink=3 --shrinkrefine=2 --iter=87 --mask=mask.sharp:outer_radius=36 --npeakstorefine=16 --preprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --align=rotate_translate_3d:search=4:dphi=12:delta=12 --parallel=thread:24 --ralign=refine_3d_grid:delta=3:range=12:search=2 --averager=mean.tomo --aligncmp=ccc.tomo --raligncmp=ccc.tomo --saveali --savesteps -v 2 --postprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --autocenter --exclusive_class_min=8 --normproc=normalize |
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| Let's explore the FIRST APPROACH. | |
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| === OPENING A TOMOGRAM DIRECTLY WITH e2tomoboxer.py === | == Monstrous command for e2spt_sim.py == e2tomosim.py --input=../groRef_scaled_bin2.hdf --snr=5 --nptcls=2 --tiltstep=5 --tiltrange=60 --transrange=10 --saveprjs --noiseproc=math.addnoise |
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| === USING THE WORKFLOW FOR SPT === | == Monstrous command for e2spt_resolutionplot.py == e2spt_resolutionplot.py --vol1=half1avg.hdf --vol2=half2avg.hdf --output=whatever3.txt --npeakstorefine=1 --verbose=3 --shrink=3 --shrinkrefine=2 --mask=mask.sharp:outer_radius=36 --preprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --align=rotate_translate_3d:search=4:dphi=30:delta=30:sym=icos --parallel=thread:8 --ralign=refine_3d_grid:delta=15:range=30:search=2 --aligncmp=ccc.tomo --raligncmp=ccc.tomo --postprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --normproc=normalize --sym=icos |
Single Particle Tomography in EMAN2
Wednesday - P.M.
This session will cover the new tools for single particle tomography in EMAN2. Unfortunately, this technique is very memory-intensive and compute-intensive. The 3 gb of ram available on the workshop computers is barely sufficient to do some small examples, and full 3-D alignments of large sets of particles can take many hours of computation.
So, for purposes of the tutorial, we will learn how to use the particle picker, and do a couple of small examples which can be completed in the available time.
DATA
TUTORIAL DOCUMENT
Not available here for now. Get it through this site:
http://blake.bcm.edu/emanwiki/Ws2011/Agenda
Monstrous command for alignment with e2classaverage3d.py
e2classaverage3d.py --input=e15pp_set1_stack.hdf --output=e15pp_set1_aligned.hdf --ref=e15ref_prep_icos_bin2.hdf --npeakstorefine=1 -v 3 --mask=mask.sharp:outer_radius=48 --preprocess=filter.lowpass.gauss:cutoff_freq=.02 --align=rotate_translate_3d:search=10:delta=8:dphi=8:verbose=1:sym=icos --parallel=thread:2 --ralign=refine_3d_grid:delta=3:range=9:search=2 --averager=mean.tomo --aligncmp=ccc.tomo --raligncmp=ccc.tomo --shrink=3 --shrinkrefine=3 --savesteps --saveali --iter=8 --normproc=normalize --sym=c1 --keep=0.8 --path=whatever_folder_I_want
Monstrous command for alignment with e2tomoallvsall.py
e2tomoallvsall.py -v 1 --path=AVSAs087 --input=CENTEREDvsD8aliVSapo_s087.hdf --shrink=3 --shrinkrefine=2 --iter=87 --mask=mask.sharp:outer_radius=36 --npeakstorefine=16 --preprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --align=rotate_translate_3d:search=4:dphi=12:delta=12 --parallel=thread:24 --ralign=refine_3d_grid:delta=3:range=12:search=2 --averager=mean.tomo --aligncmp=ccc.tomo --raligncmp=ccc.tomo --saveali --savesteps -v 2 --postprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --autocenter --exclusive_class_min=8 --normproc=normalize
Monstrous command for e2spt_sim.py
e2tomosim.py --input=../groRef_scaled_bin2.hdf --snr=5 --nptcls=2 --tiltstep=5 --tiltrange=60 --transrange=10 --saveprjs --noiseproc=math.addnoise
Monstrous command for e2spt_resolutionplot.py
e2spt_resolutionplot.py --vol1=half1avg.hdf --vol2=half2avg.hdf --output=whatever3.txt --npeakstorefine=1 --verbose=3 --shrink=3 --shrinkrefine=2 --mask=mask.sharp:outer_radius=36 --preprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --align=rotate_translate_3d:search=4:dphi=30:delta=30:sym=icos --parallel=thread:8 --ralign=refine_3d_grid:delta=15:range=30:search=2 --aligncmp=ccc.tomo --raligncmp=ccc.tomo --postprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --normproc=normalize --sym=icos