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| == Single Particle Tomography in EMAN2 == === Wed PM Practical === |
= Single Particle Tomography in EMAN2 = == Wednesday - P.M. == |
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| This is a relatively new feature in EMAN2. This session will cover the beta version of a small fraction of the Single Particle Tomography (SPT) capabilities that will eventually be available. | 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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| The session will cover: 1) Sub-volume extraction from tomograms using e2tomoboxer.py 2) Preparation of extracted particles for alignment 3) Reference based alignment and averaging |
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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| The software is provided as part of EMAN2 (already installed). | == DATA == [[attachment:e2spt_data.zip| e2spt_data.zip|&do=get]] |
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| [[attachment:spt_demo_2011.tgz]] | == TUTORIAL DOCUMENT == Not available here for now. Get it through this site: |
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| We have prepared some sample data. The tomogram in the link below comes from a tilt series of epsilon15 virion particles recorded using Zernike phase-plate technology: |
http://blake.bcm.edu/emanwiki/Ws2011/Agenda |
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| [[attachment:e15phaseplate.rec]] | == Monstrous command for alignment with e2classaverage3d.py == |
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| The following tomogram also comes from a tilt series of epsilon15 virion particles but was recorded under conventional cryoEM imaging conditions: | 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 --averager=mean.tomo --aligncmp=ccc.tomo --raligncmp=ccc.tomo --shrink=3 --shrinkrefine=3 --savesteps --saveali --iter=8 --normproc=normalize --sym=c1 --keep=0.8 |
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| [[attachment:e15normal.rec]] | == Monstrous command for alignment with e2tomoallvsall.py == e2tomoallvsall.py -v 1 --path=sptAVSAs605om36im18lp50 --input=s605allALItoAPO.hdf --shrink=3 --shrinkrefine=3 --iter=605 --mask=mask.sharp:outer_radius=36:inner_radius=18 --preprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --align=rotate_symmetry_3d:sym=d8 --parallel=thread:8 --ralign=None --averager=mean.tomo --aligncmp=ccc.tomo --raligncmp=ccc.tomo --saveali --savestep -v 2 --postprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --autocenter |
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 --averager=mean.tomo --aligncmp=ccc.tomo --raligncmp=ccc.tomo --shrink=3 --shrinkrefine=3 --savesteps --saveali --iter=8 --normproc=normalize --sym=c1 --keep=0.8
Monstrous command for alignment with e2tomoallvsall.py
e2tomoallvsall.py -v 1 --path=sptAVSAs605om36im18lp50 --input=s605allALItoAPO.hdf --shrink=3 --shrinkrefine=3 --iter=605 --mask=mask.sharp:outer_radius=36:inner_radius=18 --preprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --align=rotate_symmetry_3d:sym=d8 --parallel=thread:8 --ralign=None --averager=mean.tomo --aligncmp=ccc.tomo --raligncmp=ccc.tomo --saveali --savestep -v 2 --postprocess=filter.lowpass.gauss:cutoff_freq=.02:apix=4.401 --autocenter