Starters guide - Revision history

Raffaele Coray at 12:41, 2 December 2024

2024-12-02T12:41:55Z

2024-12-02T12:40:40Z

2024-05-20T08:17:15Z

Seeds for MRA projects

2024-05-20T08:16:45Z

Seeds for MRA projects

2021-09-06T14:39:45Z

2020-08-25T15:32:08Z

Numerical parameters

2020-08-25T15:31:18Z

Numerical parameters

2020-08-25T14:50:43Z

Loading particle in dgallery

2017-11-28T15:08:45Z

Subtomogram alignment and averaging

2017-11-28T15:08:00Z

Initial model generation

@@ Line 199: / Line 199: @@
 ==== Seeds for MRA projects ====
 * Go to “table” and type <tt>data_classification/real.tbl</tt> into the “clone this” field and press “copy”, press “OK”.
-* Go to “template” and clone data_classification/original_template.em with addition of some extra noise with amplitude 1.
+* Go to “template” and clone <tt>data_classification/original_template.em</tt> with addition of some extra noise with amplitude 1.
 * Initialize masks with the defaults parameters (large button on the bottom).

@@ Line 199: / Line 199: @@
 ==== Seeds for MRA projects ====
 * Go to “table” and type <tt>data_classification/real.tbl</tt> into the “clone this” field and press “copy”, press “OK”.
-* Go to “template” and clone data_classification /original_template.em with addition of some extra noise with amplitude 1.
+* Go to “template” and clone data_classification/original_template.em with addition of some extra noise with amplitude 1.
 * Initialize masks with the defaults parameters (large button on the bottom).
 Go to “numerical parameters” and use Predefined profiles -> refinement. Increase angular search steps to 5, set a thresholing policy and press “OK”. Set computing environment to GPU (under Matlab), specify GPU identifiers.
 ==== Execution of projects ====

@@ Line 8: / Line 8: @@
 * Avoiding overfitting via independent half dataset refinement (“gold standard processing”)
+Streamlined workshop version of this tutorial: [[Starters_guide_(workshop_version)| here]].
 ==Introduction==

@@ Line 160: / Line 160: @@
 [[File:StartersGuideFigure10.png|thumb|center|600px| Figure 10. Summary of numerical parameters used for sub tomogram averaging.]]
-Go to Computing environment in Wizard and select CPU (without Matlab). Click “Info (nvidia)” it should output you a table to your Matlab window, your GPU identifiers are in the left column of the table. Put those into the GPU identifiers to the ‘identifiers” field.
+Go to Computing environment in Wizard and select Matlab-CPU. Click “Info (nvidia)” it should output you a table to your Matlab window, your GPU identifiers are in the left column of the table. Put those into the GPU identifiers to the ‘identifiers” field.
 ====Running the project====

@@ Line 113: / Line 113: @@
 For initial model generation we will use dynamo_gallery to generate initial orientations for some of our particles. Type
-  <tt>>> dgallery(‘data’, ‘exampleData’); </tt>
+  <tt>>> dgallery(‘data’, ‘exampleData.Data’); </tt>
 assuming you named <tt>exampleData</tt> your data folder while cropping.
@@ Line 119: / Line 119: @@
 * Load particles into memory by clicking “load” in the Load from disk field on the left of the window.  Note that at first, the scene will show only '''one''' particle.
 * Display some or all of the particles with the slider in the <tt>Shown</tt> particles field on the top of the window.
 * Toggle between X- Y- and Z-views in the View: orientation field.
 ==== Manual alignment of particles in <tt>dgallery</tt> ====

@@ Line 107: / Line 107: @@
 ===Initial model generation===
-If you don’t have an initial model it is easy to generate it by manually aligning several particles and summing them up. ''Dynamo'' stores information about the particles in dynamo tables: for each particle a table contains shifts and rotations to bring the particle to the average (by default these values are initialized as 0s), particle ID (tag), orientation of the missing wedge and others. For full info type <tt>>> dthelp</tt> in Matlab. ''Dynamo'' catalogue generates an initial table during particle extraction, its location is particles/crop.tbl. For initial model generation we will use dynamo_gallery to generate initial orientations for some of our particles. Type
+If you don’t have an initial model it is easy to generate it by manually aligning several particles and summing them up. ''Dynamo'' stores information about the particles in dynamo tables: for each particle a table contains shifts and rotations to bring the particle to the average (by default these values are initialized as 0s), particle ID (tag), orientation of the missing wedge and others. For full info type <tt>>> dthelp</tt> in Matlab. ''Dynamo'' catalogue generates an initial table during particle extraction, its location is <tt>particles/crop.tbl </tt>
   <tt>>> dgallery(‘data’, ‘exampleData’); </tt>