Pipelines for Workshop Heidelberg 2018

These materials describe the procedural steps required for high resolution tomography.

Pipeline

Input data

We will start with two tilt series. A drift correction has already been applied on each tilt using motioncorr2, so that each micrograph in a tilt series is an averaged movie. The pixel size is 2.7A (the tilt series have been binned by fourier cropping to ease the computation ), and the structures of interest form spherical lattices.

Procedural steps

Preprocessing steps

As we will initially work with already drift-corrected tilt series,

• Defocus estimation with ctffind4
• Alignment of tilt series with Dynamo
• Exposure filter on the aligned tilt series.
• Stripe-based CTF correction (with ctfphaseflip from Imod)
• Creation of tomograms with Dynamo

These preprocessing operations that go from the tilt series to the tomograms can be used for any sample.

Tomogram management

This part is specific to the particular geometry of the proteins of interest.

• Cataloguing the tomograms (archiving)
• Annotation of vesicle positions.
• Extraction of putative particles based on the vesicle positions.
• Ellimination of repeated particles.

Subtomogram averaging

• Extraction of true particles.
• Splitting in odd and even data sets.
• Independent alignment and resolution determination.

Material organization

The data corresponding to each tilt series is under the folders work/1 and work/2. Intermediate results corresponding to each tilt series will be stored in the corresponding folders.

The initial structure of the folder contains two items

 ls work/1
rawStack.mrc
nominalTilts.tlt

The additional processing steps will gradually generate more elements pert tilt.

Copying data to your account

You will need to copy the provided data into you account:

cp -r /g/embl/workshop/teach11/data/work  .  

Matlab environment

Matlab provides a convenient syntax for manipulation of sets of paths.

Preprocessing

Each of the preprocessing steps can be computed separately for each tilt series. We have thus provided a set of functions, each one a wrapper that accepts as input one index that identifies a tilt series and creates an output with the right naming convention. They are intended to be callable on a loop like:

 for i=1:2
emboFunction('work',i);
end 

If new tilt series are added to increase resolution, you just need to apply the function on additional indices.

defocus estimation

The function emboDefocusEstimation will run ctffind4 on the input data, creating the following items

• Input:
• Output:

tilt series alignment

• Input:
• Output:

dose filtering

• Input:
• Output:

CTF correction of tilt series

• Input:
• Output:

Reconstruction of tomogram

• Input:
• Output: