Particle picking¶

nextPYP implements several strategies for particle picking from 2D micrographs and 3D tomograms

Method 1: Manual picking (2D and 3D)¶

2D

Inside the Pre-processing block, go to the Micrographs tab
Create a new list by clicking New, typing a name for the list and clicking Create
Select particles by clicking on their centers
Navigate to other micrographs, add additional particles as needed

3D

Inside the Pre-processing block, go to the Reconstruction group in the Tilt Series tab
Create a new list by clicking New, typing a name for the list and clicking Create
Scroll through the tomogram and select particles by clicking on their centers in 3D
Navigate to other tilt-series, add additional particles as needed

Tip

You can remove particles from a list by right-clicking on a marker
Particle lists are saved automatically every time you add or delete a particle
You can copy an existing list using :badge:Copy,badge-primary`, delete an existing list using Delete, or load a list using Load

Method 2: Size-based picking (2D and 3D)¶

This method only requires specifying the radius of your particles:

On the Pre-processing block, click on the icon and choose the Edit option
Go to the Particle detection tab and select auto as the Detection method
Set the value of the Detection radius to the expected particle size
(optional) Adjust parameters for particle detection
Click Save, then Run

This will run particle picking on all micrographs or tilt-series in the dataset and the results will be displayed inside the Pre-processing block

Tip

After the run is finished, the total number of particles in the dataset will be shown in the project information area (top left of the page)

Method 3: Geometry-based picking (3D only)¶

This mode is designed to be used for picking membrane proteins from the surface of virions or vesicles:

Step 1: Virion detection¶

On the Pre-processing block, click on the icon , choose the Edit option, and go to the Virion/spike detection tab

There are three modes available for virion picking:

Manual

We will assume that you already have a list of manually picked virion centers (see Method 1 above)
Select manual as the Virion detection method
Select the list of virion centers from the Select list of positions drop-down menu (top of the form)
Click Save, then Run to detect virions on all tilt-series in the dataset

Size-based

Select auto as the Virion detection method
Set the desired Virion radius
(optional) Adjust virion picking parameters
Click Save, then Run to detect virions on all tilt-series in the dataset

Neural-network

We will assume that you already have a list of manually picked virion centers (see Method 1 above)
Select pyp-train as the Virion detection method
Select the list of virion positions from the Select list of positions drop-down menu (top of the form)
(optional) Go to the Training/evaluation tab and adjust the training parameters
Click Save, then Run and wait for the training to finish
Go to the Virion/spike detection tab
Select pyp-eval as the Virion detection method
Go to the Training/evaluation tab and specify the Trained model obtained in the previous step by clicking on the icon and navigating to the train/ folder inside the Pre-processing block. Each training run will be saved in a separate folder (named with the timestamp YYYYMMDD_HHMMSS), where multiple intermediate models in .pth format will be available.
Click Save, then Run to detect virions on all tilt-series in the dataset

Step 2 (optional): Virion segmentation¶

Virion segmentation consists in finding a closed surface around the virion centers that follows the membrane density. nextPYP simplifies this process by calculating an implicit representation of the surface that only requires specifying one of several threshold values to detect the virion membrane. In many cases, the default value for the threshold gives reasonable results, but users can also manually select different thresholds using the web-based GUI

Inside the Pre-processing block, go to the Tilt-series tab, and select the Segmentation group
Select a virion from the table to show its 3D slices and the segmentation thresholds (8 different thresholds are shown as yellow contours in columns 1-8). The highlighted column number represents the current threshold selection (default is 1, click on a different column to select a better threshold). If none of the columns look reasonable (or if you want to ignore the current virion), select the last column labeled as “-“
Repeat this process for all virion in the tilt-series and all tilt-series in the dataset

Note

The virion threshold selections are saved automatically every time you click on a column

Step 3: Spike picking¶

There are two methods for picking spikes on the surface of virions:

Constrained template search

Set Spike detection method to template search
Specify a Spike search template using the file picker (must be .mrc format). The bottom z-slice of the template will be placed exactly at the membrane plane to carry out the search.
(optional) Adjust parameters for the template search

Uniformly spaced positions

Set Spike detection method to uniform
(optional) Adjust the parameters for uniform picking

Click Save, then Run to pick spikes on all virions in the dataset

Inspect the results by clicking inside the Pre-processing block (Tilt-series tab, Reconstruction group)

Tip

For well behaved datasets, Steps 1-3 can be run without user input in the same pre-processing run

Particle picking

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