Notes related to Electron Microscopy

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Install notes

(Assumes Ubuntu/Debian for package installation)

Dependencies

Installing dependencies for most of the things mentioned below, in ubuntu:

sudo apt-get install \
  tcsh csh \
  openmpi-bin libopenmpi-dev \
  gcc g++ gfortran gobjc build-essential cmake subversion \
  libpng-dev libjpeg62 libfftw3-bin libfftw3-dev \
  libgnomecanvas2-0 libfreetype6-dev libxml2-dev \
  libquadmath0 libxslt1-dev  libxss-dev libgsl0-dev \
  libx11-dev libxft-dev  libssl-dev libxext-dev libxml2-dev libreadline6 \
  python-numpy python-scipy python-pmw python-dev libglew-dev python-wxgtk2.8 \
  openjdk-7-jdk \
  gnuplot pdftk \
  nvidia-cuda-toolkit

Potential conflicts

Some of these packages break common library and path conventions, which sometimes break each other, and sometimes even the system.

So I like to isolate them. Basically, have only one of these overrides in a specific shell (because few users mix them).

Isolating can also be nice to switch users between multiple versions, e.g. when upgrading without "yeah, hang on for an hour" explanations.

Potential conflicts happen mostly when software

adds libraries that are already present, and with more prescedence than whatever is there

use of LD_LIBRARY_PATH (rather than ld.so config) is this, sort of per definition

it usually shouldn't lead to problems, but in some cases it can

which you can solve in part by putting these entries in the ld.so configuration instead.

adds commands that are already present, and with more prescedence than whatever is there

most commonly adding its own python install and PYTHONPATH (without virtualenving)

Potential trouble cases (based purely on what its init scripts do) include:

EMAN2 (overrides with its own python)
Xmipp (overrides with its own python)
Scipion (overrides with its own python)
IMAGIC (overrides with its own MPI)
Spring (overrides with its own python)
Dynamo (potentially with a real matlab, or is it fine?)
IMOD (LD_LIBRARY_PATH)

One easy way to make the initialization of these exclusive, that users may understand well enough, is to tell them e.g.

the following software is available once activated
  EMAN2         activate-eman2
  Scipion       activate-scipion
  IMAGIC        activate-imagic

Where, in bash,

function activate-eman2 {
  # the actual sets / sources, in this case
  source /usr/local/EMAN2.12/eman2.bashrc
}

User convenience note: In cases where you the first command is very predictable (e.g. shell-based cases like IMAGIC), you can actually do this transparently on the first run, e.g.

function i {
  # the actual sets / sources
  source $IMAGIC_ROOT/env
 
  # change i to now be the actual start, and start it 
  alias i=$IMAGIC_ROOT/imagic.e
  i
}

ACE2

Unpack.

There is a binary, but you probably want to

make

it so it links with your installed version of objective C.

...and install objective C if you didn't have it.

appion-protomo

bsoft

To install:

(see also its README)

Install instructions vary between versions, so make sure you're following the right ones.

Caltech Tomography Database

Install

This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)

Has optional separation between hosts that:

do storage (only real requirement is visibility from all the below)
run MySQL to store dataset details
do data processing
web-serve the interface

...and you can run two webservers, to have a split between "all datasets" and "datasets easily viewed/shared outside"

Installation is broadly: Storage host:

have space
share space space (probably CIFS, maybe NFS. If NFS, consider/plan UID details before you start)
make others mount it (at
/tomography/data/
or elsewhere if you change that in the scripts)

If you want to use the IMOD "Grab with notes" plugin, create the

Caps/

directory under that

Server (assuming web and database on the same):

database:
- install MySQL
- import
  DB-tomography.sql
  (creates database called tomography)
- create mysql user for web interface and give it access to this database
- manually add groups, users, names of microscopes, acquisition software (see docs for details why and how)

(optional: install phpmyadmin to make this easier

install web server (probably apache) and PHP
serve interface PHP scripts
- make sure
  tmp
  and
  workbox
  subdirectories exist and are writable (They extract with 777 permissions so should be fine)
- edit
  msql_connect.php
  to reflect the MySQL login you just made

Processing host

set up a user login to set up jobs - physical access and/or SSH

install Python/MySQLdb, ffmpeg, convert (imagemagick); IMOD (implies RAPTOR), Bsoft

Note: on RHEL, a static build of ffmpeg seems to be easier (or use RPM Fusion)

installing PBS is recommended to run multiple jobs sequentially

...though not really necessary - you could just run the script directly

create
/home/db_proc/
and make it writable (this is temporary files, and only leaves files for failed jobs)
check that the scripts can write to the data directory

i.e. run with and/or without PBS

unpack
pipeline.tgz
somewhere
- tweak
  db_inc.py
  - set MySQL connection data to your db/username/pass
  - set storage directory (default is "/jdatabase/tomography/data/")

look at
db_proc.py
- if no PBS, it needs some tweaking (what exactly? (verify))
- if using real-time mode, look whether you're happy with the the timeout

broadly tweak
db_proc.pbs
for your setup, then tell users to use it as a template
- alter
  exepath
  to reflect where you put the scripts
- suggestions for site-specific details, e.g. valid values of software_acquisition

(there's also a .pbs for reconstruction, you can ignore that one until you need it)

Assuming Ubuntu and that you're putting all parts on the same host, a good start is:

sudo apt-get install apache2 libapache2-mod-php php-mbstring php-mysql mysql-server phpmyadmin python-mysqldb \
  ffmpeg imagemagick \
  torque-server torque-mom torque-pam

For torque PBS, see e.g. https://jabriffa.wordpress.com/2015/02/11/installing-torquepbs-job-scheduler-on-ubuntu-14-04-lts/

These scripts seem to be tied to its initial install. They will need changes to work elsewhere, e.g.

hardcoded hostnames

fixed by changing names or removing "am I running here?" checks

assumption PBS provides other tools in the PATH

will also break without IMOD_DIR being set. fixed via sourcing a file specific to your setup

hardcoded paths to various tools

fixed by looking around, mostly in the db_proc*.py Could remove absolute paths if you're fixing via a file you source.

RAPTOR may require a path to itself? Not sure how IMOD is supposed to work here...

assumptions that turn out to be fragile

e.g. check_mrc breaks with some bsoft versions due to it reading text output and that having changed mildly.

Most of that can be done in db_proc.py / db_proc_mc.py

Use and testing

This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)

Once set up, most browsing interaction is done via the web interface.

A single dataset('s pipeline) is started va the shell, though.

logging into the processing machine

(if you don't have your storage place mounted) uploading data involves getting a script that runs rsync or such

copy template .pbs script to yourprojectname.pbs

probably to a directory specific to this, purely to avoid a mess

edit it for the specific project

INPUTDIR

="/where/to/look/for/mrc/files"

tomo_date

="yyyy-mm-dd"

wait_for_new_tilt

=1 to keep waiting for new files (u[p to a certain configured time), or =0 to terminate after a single pass

userid

- an existing user ID (simple setups will have just one, in which case it can be in the template and you can just leave it)

collection and reconstruction parameters

qsub yourprojectname.pbs

Check for results in interface's Inbox

Notes:

after a tilt series (mrc) is processed, it will be moved under INPUTDIR/Done (verify)

unsuccessful RAPTOR outputs are left under /home/db_proc/ so you should check this occasionally

ctffind

Keep in mind that the latest (currently 4.1) may be in beta and not on the general download page.

See also:

Chimera

The linux version comes as a self-extracing archive, which asks you

where to extract
whether to register a .desktop link and icon (apparently using its bin/xdg-setup)
whether to create a link in a common bin directory

Diplib

The easiest way to always have diplib run at startup is to find

toolbox/local/matlabrc.m

and add:

addpath('/opt/dipimage/common/dipimage')
dip_initialise

Some shared objects will have to be where Matlab looks. If you only do the above, it'll say where.

Dynamo

Download: https://wiki.dynamo.biozentrum.unibas.ch/w/index.php/Downloads

Install:

https://wiki.dynamo.biozentrum.unibas.ch/w/index.php/Installation

and its README_dynamo_installation.txt

Using the GPU means linking against your installed CUDA, roughly:

edit cuda/makefile to update CUDA_ROOT and CUDA_LIB (on my system it's

/usr

and

$(CUDA_ROOT)/lib/x86_64-linux-gnu/

respectively)

run

make motors

(I have this problem, which went away when I made the active gcc 5 instead of 7)

See also:

https://wiki.dynamo.biozentrum.unibas.ch/w/index.php/Main_Page

EMAN2

≤2.12

After files are installed, it runs

eman2-installer

to create the shell script you should source.

This also seems to alter the hardcoded paths in the hashbangs, so you should re-do this if you move the installation.

=2.2

Add its bin to the PATH (the installer asks whether to do so in your .profile)

ImageJ / Fiji

IMOD

If you want control over where it goes, run the installer like:

bash imod_4.9.0_RHEL7-64_CUDA6.5.sh -dir /opt -name imod-4.9.0 -skip

Where

-dir is base directory, where the following is created under (defaults to /usr/local)

-name is handy if you are versioning different installations

-skip means it won't link it into /etc/

...which I do because I want to manage this myself - amounts to:

export IMOD_DIR=/opt/imod-4.9.0

source $IMOD_DIR/IMOD-linux.sh

note: the sourced file will take IMOD_DIR from the environment (when not set it will fall back to the path that it originally installed under)

before ~v4.9 or so it required tcsh (even if you already have csh)

Notes:

If the installer tells you
Syntax error: "(" unexpected
, this is due to the installer assuming that /bin/sh is specifically bash (on some distros it's dash)

You can work around this by explicitly running with bash as above, or editing the first line to say #!/bin/bash

Install notes seem to suggest that the most predictable environment for IMOD binary is Redhat/fedora, in a VM if you don't naturally run that.

It seems perfectly fine on debian / ubuntu, though CUDA is a little different.

See also:

http://bio3d.colorado.edu/imod/doc/guide.html

Config

Via files

One alternative is to store host-specific config in files.

It looks in the directory set in $IMOD_CALIB_DIR

It defaults to /usr/local/ImodCalib, unless it was set already (this logic is in the file you source)

that default directory isn't created at install time, so you may need to

then copy things there

this is mostly about cpu.adoc -- which you'll want to use parallel processing and/or GPU

Via environment

Instead of using cpu.adoc you can also set many things via environment variables, e.g.

export IMOD_DIR=/opt/imod
export IMOD_CALIB_DIR=$IMOD_DIR/autodoc
export IMOD_PROCESSORS=16
source $IMOD_DIR/IMOD-linux.sh

While you can't do as much with this, it can be simpler if all you need to set are amount of CPU cores

If you want GPU processing,

make sure CUDA is installed and working (recent IMOD seems to want ≥ CUDA 6 (verify))
set gpu.device=1 in cpu.adoc, or use the equivalent environment variable (0 seems to refer to best?)
or e.g. gpu.device=1,2,3,4 if you have four; see also [1]

make sure the device is accessible by the effective user. chmod 666 /dev/nvidia* is probably easiest (SUID root should also work)
testing:

gputilttest

If it fails, look at the log

PEET

This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)

See http://bio3d.colorado.edu/ftp/PEET/INSTALL.TXT

Example:

cd /opt
mkdir PEET 
cd PEET
wget http://bio3d.colorado.edu/ftp/PEET/linux/Particle_1.10.1_linux.tar.bz2
wget http://bio3d.colorado.edu/ftp/PEET/linux/ParticleRuntimeV84_linux.tar.bz2
tar xvf Particle_1.10.1_linux.tar.bz2
tar xvf ParticleRuntimeV84_linux.tar.bz2

Edit

Particle/particle.cfg

edit the MCR_ROOT line, as it it hardcodes the path to ParticleRuntime
It putting its libraries in front of the existing LD_LIBRARY_PATH can break other programs, you may want to change that.

Edit

Particle/Particle.sh

(or the variant you use)

edit the PARTICLE_DIR line, it hardcodes its own path

Ensure the relevant users will source this last file.

parallel processing, and multi-node processing

This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)

Parallel execution is done by processchunks (usually run via a GUI):

"processchunks will process a set of command files in parallel 
on multiple machines or processors
that have access to a common filesystem.
It can also be used to run a single command file on a remote machine."

For local parallel processing, use cpu.adoc that at least has number= saying how many parallel processes to run.

Running on multiple hosts amounts to:

cpu.adoc with a section for each host (see the cpuadoc man page for more details)

passphraseless ssh logins to each (same user(verify))

a shared filesystem

(and, if it are mounted at different places on different hosts, telling IMOD about that. See the "Mount Rules for Local to Remote Path Translations" section in the cpuadoc man page)

It remotely runs commands wrapped in something like:

ssh hostname bash --login -c '"command"'

...which means you may want to place your sourcing of imod environment in a profile.d file for convenience. See also [2]

See also:

http://bio3d.colorado.edu/imod/doc/guide.html#ParallelProc

On windows

localrec

Seems to leverage relion and scipion (though not relion via scipion - it e.g. wants to see relion on the path, which is not something scipion does itself).

Wants to

have its /lib on the PYTHONPATH (see "how to install")
see relion ≥1.4
be run via scipion ≥1.0.0

like

scipion run relion_localized_reconstruction.py

(probably start with -h)

See also:

motioncorr

MotionCor2

Binary, fairly static compiles.

Older versions depend on libtiff3, which is either too old to be available in some distros. Usually it works well enough to copy the .sofile alongside (see also libtiff naming).

Also a potential issue with libjbig, depending on distro.

Newer versions require CUDA 8 minimum, which can be a pain on older systems.

Note also the docs say "We recommend 128 GB or more CPU memory, although 64 GB CPU memory is also workable."

Pymol

Wants admin rights to install into system dirs

Pytom

Install dependencies

Get the source

git clone --depth=1 http://git.code.sf.net/p/pytom/gitrepo pytom

Compile:

cd pytom/pytomc
# NOTE: needs to be tweaked to your system:
./compile.py \
  --includeDir /usr/include/python2.7 /usr/lib/openmpi/include /usr/include/boost/ /usr/lib/python2.7/dist-packages/numpy/core/include/numpy/ \
  --libDir /usr/lib/openmpi/lib /usr/lib /usr/lib/x86_64-linux-gnu/ \
  --dirPath /usr/lib/openmpi/bin \
  --pythonVersion 2.7 \
  --target all

See if setup will work

cd pytom/pytomc
./check.py

(in my case I got the word too long issue because of a long PATH - it seems pytom copies the current path into bin/paths.csh - so edit that to remove a bunch of stuff that pytom doesn't need anyway)

See also:

Relion 3

For specific versions, see https://github.com/3dem/relion/tags

Relion has to be compiled, which may be relatively painless, sometimes less so.

install prerequisites, on debian/ubuntu amounts to something like:

sudo apt-get install build-essential openmpi-bin libopenmpi-dev libx11-dev g++ libtiff-dev xorg-dev libfftw3-dev

(not entirely sure about xorg-dev, but it seems to want it to compile FLTK)

build

cd /opt/relion-src/  # wherever you unpacked it
mkdir build
cd build
cmake ..             # but there are tweaks you may wish to add here - see below
make -j 8            # means 'use 8 CPUs for compilation when you can', doesn't matter so much but hey
make install

Once built,make usable usable by putting binaries and libaries where they can be found, e.g.

export PATH=$PATH:/opt/relion-src/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/relion-src/lib

Optional but useful: it's rather convenient when relion fills in where certain executables are via environment variables, e.g.

RELION_MOTIONCORR_EXECUTABLE

RELION_MOTIONCOR2_EXECUTABLE

RELION_CTFFIND_EXECUTABLE

RELION_GCTF_EXECUTABLE

...and more, see [3] for a list These do not have to be full paths if they are on the PATH (verify).

Build issues

Consider installing into a specific path (rather than to system directories, which is default), e.g. to keep track of distinct builds, and toggle between them, without getting horribly confused with versions. I add something like:

-DCMAKE_INSTALL_PREFIX=/opt/relion-3.0b

gcc <6 apparently, or ≤5 maybe? Certainly gets confused by 7.

If you have multiple gcc versions installed, and you don't want to make an old one the default, then you need to point the build at a specific one, e.g. add:

-DCMAKE_C_COMPILER=/usr/bin/gcc-5 -DCMAKE_CXX_COMPILER=/usr/bin/g++-5

CUDA - installed and working.

As far as I can see, GPU features are only built if detected at compile time. It may get confused if you have multiple CUDA installs.

compute capability defaults to 3.5, for compatibility. You can set it higher (e.g. -DCUDA_ARCH=52) though I've not checked how much difference it makes.

If you get the "‘memcpy’ was not declared in this scope" error, then you're probably using gcc5. Edit build/CMakeCache.txt and add _FORCE_INLINES to one of the flag strings that gets it to where it needs to be (CMAKE_NVCC_FLAGS works, as does generic c flags):

CMAKE_NVCC_FLAGS:STRING=-D_FORCE_INLINES

MPI

basically, try to run

mpirun

and

mpiCC

. If you get "file not found" or such, install the relevant packages.

if the build process can't find MPI and it is there, this seems to be a cmake change/bug [4] and you want and older one, like 3.9.6 (Copy the contents into /usr, no compilation of it is necessary). Ubtuntu 18 has a newer one so you'll need to do this until this is fixed in relion.

Also, be careful of multiple version of MPI (or libtiff) being installed. I've e.g. had trouble with EMAN2 and bsoft messing things up.

See also:

Scipion

Scipion is a package from the Spanish CNB (Centro Nacional de Biotecnología) in Madrid.

It tries to wrap and integrate various major EM software packages, in a pluggable way. XMIPP is now (only) part of this package.

Installing from source

You can download a binary, or build from source. Source is the way to get the latest.

Install build dependencies

# for debian/ubuntu it's roughly
sudo apt-get install gcc g++ cmake libtiff-dev libxft-dev libssl-dev libxext-dev libxml2-dev libreadline6 \
 libquadmath0 libxslt1-dev  libxss-dev libgsl0-dev libx11-dev gfortran libfreetype6-dev \
 libopenmpi-dev openmpi-bin openjdk-8-jdk

(possibly specific gcc/g++ versions, see notes below)

Get the source

git clone https://github.com/I2PC/scipion.git scipion-src

Install / update Go to the directory you downloaded/installed it

cd /opt/scipion-src

First time: prepare build

./scipion config

edit config/scipion.conf (usually the only thing you need to check, at least on a new install)

e.g. MPI, java, and maybe CUDA details

In some cases there are other configs to edit, e.g. config/hosts.conf if you're running on a cluster, and config/protocols.conf if you already knew you need to (not on standard installs)

Build

./scipion install -j 5

Note: Scipion is tied to xmipp, and installs it by default. If you want to separately build your own xmipp (e.g. to keep up to date with nightlies), do that first, then point scipion at that xmipp, like

./scipion install --with-xmipp=/opt/my-xmipp

Most later updates to this instance of scipion should amount to:

git pull && ./scipion install -j 5

Installing OR hooking in software

It's sort of the point of scipion that beyond xmipp you also get various other software, so most people will want (scipion) to install additional sofware (under scipion-src/software/em/name) e.g.

./scipion install motioncor2 ctffind4 Gctf Gautomatch relion frealign eman simple spider dogpicker localrec resmap summovie unblur

For a current list of the software it can install / looks for, see:

scipion install --help

Note that if you are the admin installing and updating many packages yourself, you can avoid some duplication by symlinking to your already-installed versions, e.g.

ln -s /opt/ctffind4 /opt/scipion-src/software/em/ctffind4
ln -s /opt/bsoft    /opt/scipion-src/software/em/bsoft
# ...etc

Build issues

On MPI:

MPI_LIBDIR should point at the directory containing the relevant (what exactly? libmpi.so?(verify))

MPI_INCLUDE should point at the directory containing the relevant mpi.h (verify)

MPI_LIBDIR should point at the directory containing mpirun (verify)

This will vary between systems. For my ubuntu system, and using the apt-installed openMPI, that means respectively:

/usr/lib/x86_64-linux-gnu/openmpi/lib/

/usr/lib/x86_64-linux-gnu/openmpi/include/

/usr/bin

beware of other (EM) software putting their MPI ahead of the system one in the PATH or LD_LIBRARY_PATH. This is a recipe for headaches.

OpenCV

If OpenCV then fails to build against CUDA, see https://github.com/I2PC/scipion/wiki/Troubleshooting

When switching to Ubuntu 16 I ran into an issue with OpenCV not finding libglib, indicated by build errors like:

libgio-2.0.so.0: undefined reference to `g_source_modify_unix_fd'

This seems to just be a library-path thing, e.g

/usr/lib/x86_64-linux-gnu/

not being in ld.so's list. Either add it in ld.so.conf(.d) (it's supposed to be in there, right?), or hack it into CMakeCache.txt

"CMake Error at cmake/OpenCVDetectCXXCompiler.cmake:89"

Seems to mean OpenCV won't compile on recent gcc7[5] The solution right now seems to be to switch to gcc6 (probably best done via the config file)

fatal error: stdlib.h: No such file or directory

Try adding -DENABLE_PRECOMPILED_HEADERS=OFF to the compiler flags in the config file. If that doesn't work, you probably messed up your compiler environment. Or maybe switching to gcc-6 or gcc-5?

For some others, see:

https://github.com/I2PC/scipion/wiki/Troubleshooting

Runtime issues

Java

Unrelated to scipion directly, but as of this writing, Ubuntu's build of openjdk-9 is currently causing a segfault (Apparently freetype using the JNI interface?), so you can't really use it.

I've also gotten issues with it erroring on StringConcatFactory. This seems to be compilation oddness which I've not yet figured out (maybe have no java9 on your system?), so I gave up and installed the scipion binary instead.

Motioncor2

It seems scipion's install assumed you have a specific CUDA version (or I'm missing some config).

If so, a quick fix is to rename the right executable to the (wrong) one it was expecting.

e2boxer

See e.g. https://github.com/I2PC/scipion/wiki/Troubleshooting#launching-eman-boxer-protocol

Installing from binary

Install dependencies - now roughly:

sudo apt-get install openjdk-8-jdk libopenmpi-dev openmpi-bin gfortran

Download from http://scipion.i2pc.es/download_form/

Follow instructions at https://github.com/I2PC/scipion/wiki/How-to-Install-1.1-bin which are roughly:

Untar the download

Do the

./scipion config

configuration, mostly for MPI (see notes above)

Install further software as needed (see the instructions)

Configure your environment for use

The environment hook-in seems to be:

# for scipion
export PATH=$PATH:/opt/scipion

# If you want to hook its xmipp for CLI use outside of scipion, add something like:
source /opt/scipion/software/em/xmipp/xmipp.bashrc
# (determines its location at runtime, so you don't have to bake in anything) 
# Note that the latter hooks in its own python environment, not virtuanlenv'd,
#   and before the system one. If that breaks things, you may want an activation alias (see above)

Notes:

Scipion also seems to assume its xmipp has a python install, while it doesn't necessarily build that (verify)

scipion-session

Spider

Spring

http://www.sachse.embl.de/emspring/install.html

If you use the packaged ('binary') version, then you will need to mostly just run:

sh patches/binary_install_linux.sh

Due to what this does, you'll probably need to run this on each PC you install on

Xmipp

This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)

From around version 3.2, you can only really install it as part of scipion, though you can still mostly use it as before.

TODO

Bsoft, bfactor, coot, ctffind3, ctffind4, motioncorr, MotionCor2, MATLAB, fiji, frealign, IHRSR, protomo, relion, resmap, situs, sculptor, spider, tigris, tomoctf, CCP4, Dynamo, IMAGIC, IMOD, PEET, phenix, Pymol

Task-specific notes

Gain correction

There is usually a factory flat field correction, e.g. based on dark-frame images and the per-pixel gain apparent from a few dozen or few hundred images.

This assumes that

the statistics of these images is enough
the defects stay constant

These are reasonable assumptions, though [1] demonstrates there are leftovers, and also non-constants like dust on the sensor. This paper's assumption is that over the term of tens of thousands of images, each pixel should behave identially in terms of mean and standard deviation, and that you can correct images towards that assumption using only those statistics - using the dataset itself.

One can argue about how influential these residuals are expected to be, but the correction is simple enough to do.

See also:

https://en.wikipedia.org/wiki/Flat-field_correction
[1] Afanasyev et al., 2015, "A posteriori correction of camera characteristics from large image data sets"

CAMERA-NORM-CORRECTION in IMAGIC

Movie-frame alignment

This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)

The beam's energy tends to induce movement in the particles (and there may be things like drift, charging).

Trying to align frames before summing them can give higher contrast and/or more information (e.g. CTF with more rings).

Software varies in assumptions and method - uniform global move or local alignment, shift-only or not, filtering to avoid near-nyquist distractions, etc.

There is some comparison in Rawson et al. (2016), "Methods to account for movement and flexibility in cryo-EM data processing"

driftcorr/motioncorr

from Yifan Cheng Lab

Called motioncorr and driftcorr (e.g. its webpage is named driftcorr and titled motioncorr, download is motioncorr*.tgz, command is dosefgpu_driftcorr (also referring to dose fractionation))

Global shift only(verify)

GPU-only.

Will need permission to the GPU, and a matching CUDA version (which one?(verify)), or will say something like "Failed to initialize GPU #0".

One way to fix the permissions:

sudo chmod 666 /dev/nvidia*

If you don't want to do that, you probably want to chown driftcorr as root:root and add SUID/SGID to give it access. (a third option would be to use sudo, but then the result files will be owned by root, which is probably annoying)

See also:

http://cryoem.ucsf.edu/software/software.html

Li et al, 2013, "Electron counting and beam-induced motion correction enable near-atomic-resolution single-particle cryo-EM"

MotionCor2

(formerly known as UcsfDfCorr)

GPU-only, as of this writing built against CUDA 7.5.

Can also read 4-bit data (as e.g. UCSF Tomo can output)

See also:

ZORRO

https://github.com/C-CINA/zorro

Alignframes in IMOD

Global shift only(verify)

Can use CPU or GPU.

Fairly flexible set of options (filtering, binning, and whatnot).

xmipp optical flow

Does localized shift analysis(verify) (after global shift).

(since xmipp 3.2, the beta version as of this writing)

Can use CPU or GPU.

See also:

Abrishami et al, 2015, "Alignment of direct detection device micrographs using a robust Optical Flow approach"

relion

Since relion is particle-oriented, it does it per-particle as an optional later step, called particle polishing

This means it does not not assume the entire micrograph has an equal shift overall, as others do. This can make more sense in that it can optimize for each particle (though can arguably also be more susceptible to mistakes, using less information).

See also:

http://www2.mrc-lmb.cam.ac.uk/relion/index.php/Process_movies#Particle_polishing

k2align

https://github.com/dtegunov/k2align

ALIGN-MOVIE-FRAMES in IMAGIC

Global shift, optional rotate. (comes from its generic alignment code).

CPU-only.

unblur / summovie

Global shift only

Exposure-dependent filter, as explained in the artucles

CPU-only (verify)

CTF estimation and correction

In packages

Various pakages have their own as part of their complete toolset, including:

IMAGIC's CTF-FIND
EMAN2's e2ctf.py,
Scipion/xmipp - see http://xmipp.cnb.csic.es/twiki/bin/view/Xmipp/ListOfPrograms#CTF_estimation_and_correction

Gctf

Statically compiled against specific CUDA libraries, so no backwards compatibility. e.g. right now if you're on CUDA9, tough cookies.

See also:

K Zhang, 2015, "Gctf: Real-time CTF determination and correction"
http://www.mrc-lmb.cam.ac.uk/kzhang/Gctf/

ctffind3, ctffind4

See also:

http://grigoriefflab.janelia.org/ctf

tomoctf

See also:

https://sites.google.com/site/3demimageprocessing/tomoctf
J Fernández, 2006, "CTF determination and correction in electron cryotomography"

Anisotropic magnification

Most methods choose to work with diffraction, i.e. crystals, because this separates it from the effects of astigmatism.

Many have specific samples. Crystalline ice can be enough, though good prep minimalizes it...

IMAGIC

A posteriori, e.g. on water rings present in the dataset (though since that's at 3.8A that's not quite trivial to do).

magdistortion

Measures on a test sample ("polycrystalline samples such as gold shadowed diffraction gratings").

See also:

http://grigoriefflab.janelia.org/magdistortion
Grant and Grigorieff (2015), "Automatic estimation and correction of anisotropic magnification distortion in electron microscopes"

correctmaganisotropy

Measures on a test sample (crystalline thallous chloride)

See also:

Some common tools

file inspection, manipulation

header (IMOD)

inspect header values

bhead (IMOD)

inspect header values

bcat (Bsoft)

newstack (IMOD)

stack operations:
- copy (when using infile outfile, as in general in imod)
- extract (when using -secs/-SectionsToRead, or fileinlist)
- append to

change data type (MODE)

can rescale densities according to range, mean-and-stdev

-replace to overwrite instead of replace

e.g. to convert/rescale a file in-place

format conversion: can output MRC, TIFF, HDF

extended header stuff:
- deal with some tile angle details
- import some .mdoc metadata (from SerialEM)

some basic processing
- binning
- anti-aliased scaledown
- fourier-based reduce, shift
- crop

e.g. create stack from images

newstack frame1.mrc frame2.mrc frame3.mrc stack.mrc
bcat     frame1.mrc frame2.mrc frame3.mrc stack.mrc

clip (IMOD)

Management and review tools

ISPyB

A Laboratory Information Management System from Diamond, aimed at synchrotrons.

Includes

Tracking shipments, sample storage
Acquisition monitoring
Review past collections
Reports
Remote access
iPhone/iPads app similar to basic web interface

See also:

Focus

Puts initial image processing close to collection, to allow remote monitoring, aimed at single particles, two-dimensional crystals, and electron tomography.

See also:

Sphire

http://sphire.mpg.de/index.html#gallery

Semi-sorted

https://en.wikibooks.org/wiki/Software_Tools_For_Molecular_Microscopy

EPU session notes

Scipion notes

Scipion and GPU / CUDA

More on protocols

Protocol: a processing task that involves the execution of or or more several steps part of a sensible whole

can execute Python code and/or call external programs

should handle conversions to/from scipion objects, in terms of metadata, arguments, input, output

declared input parameters are shown in the GUI

StringParam, FloatParam, IntParam, BooleanParam, EnumParam

PointerParam: points at objects from the database (verify)

RelationParam: points at select relations instead of objects (mainly used for CTF browsing) (verify)

ProtocolClassParam select protocol classes (used for Workflows, under development)

http://scipion.cnb.csic.es/old-docs/bin/view/TWiki/HowToDevelopProtocols

https://github.com/I2PC/scipion/wiki/Integrated-Protocols

EMAN2

e2boxer

e2boxercache: http://blake.bcm.edu/emanwiki/Eman2AppMetadata

box.type:

SwarmBoxer.REF_NAME = 'swarm_ref' (black)
SwarmBoxer.WEAK_REF_NAME = 'swarm_weak_ref' (blue)
SwarmBoxer.AUTO_NAME = 'swarm_auto' (green)
manual: white

PyMol notes

Selection of atoms is pretty nice

For the syntax and algebra, see things like [6], [7]

If you want a detailed mesh around a specific piece of chain, you often want to

[8] for a resampled mesh

You usually want to do an map_trim around a useful selection (e.g. a chain) first

first, because this increases the memory use eighfold (3D so 2*2*2), and if the reduction is large that saves space and time

You may also wish to play with mesh_width's value

http://www.pymolwiki.org/index.php/Isomesh

EM software notes

Contents

Install notes

Dependencies

Potential conflicts

ACE2

appion-protomo

bsoft

Caltech Tomography Database

Install

Use and testing

See also

ctffind

Chimera

Diplib

Dynamo

EMAN2

ImageJ / Fiji

IMOD

Config

PEET

parallel processing, and multi-node processing

On windows

localrec

motioncorr

MotionCor2

Pymol

Pytom

Relion 3

Build issues

Scipion

Installing from source

Build issues

Runtime issues

Installing from binary

Configure your environment for use

scipion-session

Spider

Spring

Xmipp

TODO

See also

Task-specific notes

Gain correction

CAMERA-NORM-CORRECTION in IMAGIC

Movie-frame alignment

driftcorr/motioncorr

MotionCor2

ZORRO

Alignframes in IMOD

xmipp optical flow

relion

k2align

ALIGN-MOVIE-FRAMES in IMAGIC

unblur / summovie

CTF estimation and correction

In packages

Gctf

ctffind3, ctffind4

tomoctf

Anisotropic magnification

IMAGIC

magdistortion

correctmaganisotropy

Some common tools

file inspection, manipulation

Management and review tools

ISPyB

Focus

Sphire

Semi-sorted

EPU session notes

Scipion notes

Scipion and GPU / CUDA

More on protocols

EMAN2

PyMol notes

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