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| 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. |
Unfortunately, this technique SPT is very computationally intensive (both in terms of memory and processing speed). 3GB of RAM is the bare minimum recommended to get through the tutorial. For more realistic SPT on full 3D alignments on large sets of large particles particles, 8GB of memory and the use of multiple processing units is advised. |
Single Particle Tomography in EMAN2
Unfortunately, this technique SPT is very computationally intensive (both in terms of memory and processing speed). 3GB of RAM is the bare minimum recommended to get through the tutorial. For more realistic SPT on full 3D alignments on large sets of large particles particles, 8GB of memory and the use of multiple processing units is advised.
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 e2spt_classaverage.py (used to be e2classaverage3d.py)
e2spt_classaverage.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 e2spt_hac.py (used to be e2tomoallvsall.py)
e2spt_hac.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
Not so monstrous command for e2spt_simulation.py (used to be e2tomosim.py)
e2spt_simulation.py --input=../groRef_scaled_bin2.hdf --snr=5 --nptcls=2 --tiltstep=5 --tiltrange=60 --transrange=10 --saveprjs --noiseproc=math.addnoise
Semi 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
Decent command for e2spt_rotationalplot.py
e2spt_rotationalplot.py --input=initModel.hdf --output=toAs129avsaAVG.txt --daz=1 --shrink=1 --dalt=180 --mask=mask.sharp:outer_radius=28
Command for e2spt_radialdensityplot.py
e2spt_radialdensityplot.py --vols=volA_aligned.hdf,volB_aligned.hdf --normproc=normalize.edgemean --lowpass=filter.lowpass.gauss:cutoff_freq=0.02:apix=4.401 --singleplot --output=volAali_VS_volBali.png