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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_e15.zip| e2spt_data_e15.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: |
[[attachment:e2spt_data_apoTRiC.zip| e2spt_data_apoTRiC.zip|&do=get]] |
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| [[attachment:e15phaseplate.rec]] | == TUTORIAL DOCUMENT == Not available here for now. Get it through this site: |
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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: | http://blake.bcm.edu/emanwiki/Ws2011/Agenda |
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| [[attachment:e15normal.rec]] | == Monstrous command for alignment with e2spt_classaverage.py (used to be e2classaverage3d.py) == |
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| == BOXING == There are two options for opening the tomogram for purposes of boxing it. |
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 |
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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. | |
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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]. |
== Monstrous command for alignment with e2spt_hac.py (used to be e2tomoallvsall.py) == |
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| Let's explore the FIRST APPROACH. | 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 |
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| === OPENING A TOMOGRAM DIRECTLY WITH e2tomoboxer.py === To launch one of the tomograms provided (you're free to choose which ever you prefer) type the following at the commandline: |
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| {{{ e2tomoboxer.py e15normal.rec --yshort --inmemory }}} |
== 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 |
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| '''To specify --yshort, or not to''' | |
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| This option will FLIP orientation of your tomogram respect to the Y and Z coordinates. You should ONLY specify it IF the tomogram has its smallest/slimmest dimension running along the Y-axis, so that it becomes parallel to the Z-axis instead. | == 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 |
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| '''Ok... but, still, WHY? What does this mean?''' | |
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| Some tomograms are built with the slimmest part of the 3D volume (that corresponding to the "ice thickness" in cryoEM) running along the Y-axis. BUT '''__in EMAN2 volumes are displayed such that the Z-axis is perpendicular to the screen__'''. Ideally, you would want the slimmest part of the volume to be aligned along Z (NOT Y) so you can view the entire tomogram "from the TOP", and look at the entire CCD-captured area in the XY plane slice by slice, as you go through the volume. |
== 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 |
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| '''--inmemory''' | |
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| This option loads your tomogram to memory, allowing to box particles (or do whatever you want to do in e2tomoboxer) more "smoothly" (faster), because reading data "from memory" is faster than reading it "from disk". You can get the entire list of options that e2tomoboxer.py takes (not many at this point) and some sort of explanation of what they're for by typing the following at the commandline: {{{ e2tomoboxer.py -h }}} === USING THE WORKFLOW FOR SPT === |
== 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 |
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 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