Difference between revisions of "Walkthrough on localized reconstruction"

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=== Binned tilt series ===
 
=== Binned tilt series ===
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We bin the original tilt series:
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<tt>ts2 = dpktilt.bin(ts,2)</tt>
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This command applies a binning of level two to the micorgraphs in the matrix <tt>ts</tt> separately. Note that the dimensions of the new matrix are floor( [sx,sy]/2<sup>2<2>).
  
 
=== Filtered  tilt series ===
 
=== Filtered  tilt series ===
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In this walkthrough, we use Weighted Backprojection as reconstruction algorithm. We apply here the simplest possible  filter onto the original projections: a ramp filter.
  
 
=== Reconstruction ===
 
=== Reconstruction ===
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As we have binned the tiltseries,  a reconstruction at the full extent of the tomogram  will fit easily in memory. We need to chose a size of the output tomogram, expressed in pixels of the stack
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By default, the center of the reconstructed volume will be located at the stack 3d center.
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<tt> orec = dpktilt.math.backproject([400,400,300],ts2,tiltAngles);</toc>
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The output <tt>orec</tt> contains the reconstructed volume (as field <tt>v</tt>), and other information, including a description of the geometrical relationship between the reconstucted volume and the tilt series. We will use this information later.
  
 
==== CTF considerations ====
 
==== CTF considerations ====

Revision as of 09:54, 1 November 2017

ARTICLE IN CONSTRUCTION, SORRY

In this walkthrough, we use localized reconstruction to reconstruct a set of subtomograms at full pixel resolution without the requirement of creating a full reconstruction first. In this approach, we:

  • create a reconstruction at low resolution
  • mark the coordinates of interest in the low resolution reconstruction
  • reconstruct separately the different coordinates at full resolution

For the sake of simplicity, in this walkthrough, the landmarks of interest will be simply the gold beads, which are trivially recognizable both in tomograms and in projections in the tilt series.

Example data set

The data set is an aligned tilt series. No filtering has been performed on it.

Source

The tilt series was used in the publication Cryo-EM structure of the extended type VI secretion system sheath-tube complex (J Wang et. al - Nature microbiology, 2017).

Download tilt series file

An aligned data set can be download from:

wget <not yet available>

This will create a file called ts.mrc in your current working directory.

Inspecting the tilt series

The tilt series at full pixel resolution can be inspected by:

dtmshow

Geometric conventions

In Dynamo, we call stack 3d center to a point (xsc, ysc,zsc) univocally defined by a stack of micrographs:

  • xsc and zsc and determined by the rotation axis implicitly defined by the alignment.
  • ysc is the center of the stack along direction y, defined as floor(Ny/2)+0.5; for a tilt series with Ny pixels along y.

Creation of a binned reconstruction

Binned tilt series

We bin the original tilt series:

ts2 = dpktilt.bin(ts,2)

This command applies a binning of level two to the micorgraphs in the matrix ts separately. Note that the dimensions of the new matrix are floor( [sx,sy]/22<2>).

Filtered tilt series

In this walkthrough, we use Weighted Backprojection as reconstruction algorithm. We apply here the simplest possible filter onto the original projections: a ramp filter.

Reconstruction

As we have binned the tiltseries, a reconstruction at the full extent of the tomogram will fit easily in memory. We need to chose a size of the output tomogram, expressed in pixels of the stack By default, the center of the reconstructed volume will be located at the stack 3d center.

orec = dpktilt.math.backproject([400,400,300],ts2,tiltAngles);</toc>

The output orec contains the reconstructed volume (as field v), and other information, including a description of the geometrical relationship between the reconstucted volume and the tilt series. We will use this information later.

CTF considerations

For simplicity, we are skipping the CTF correction step in this walkthrough, where we are only interested in the geometrical manipulations. In a real case, you would just use a version of the tilt series where each micrograph has been phase-flipped according to a defocus estimation computed on the full micrograph.

Annotation on binned reconstruction

Location of 3d annotations on 2d tilt series

Visualization

The basic tool for visualizing sets of 2d markers defined on a tilt series is dmarkers

Localized reconstruction

Reconstruct a single area

Reconstruction into a data folder

The command dtrec is the counterpart of dtcrop for tilt series. It loops on the positions inside a table