scipion-em-topaz 3.1.1

Plugin to use Topaz within the Scipion framework

This plugin allows to use Topaz programs within the Scipion framework. It can denoise, pre-process micrographs and pick particles within Scipion.

Topaz is a pipeline for particle detection in cryo-electron microscopy images which uses convolutional neural networks trained from positive and unlabeled examples.

Installation

You will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:

1. Stable version

   It can be installed in user mode via Scipion plugin manager (Configuration > Plugins) or using the command line:

   scipion installp -p scipion-em-topaz

2. Developer’s version

   • download repository

   git clone -b devel https://github.com/scipion-em/scipion-em-topaz.git

   • install

   scipion installp -p /path/to/scipion-em-topaz --devel

Topaz software will be installed automatically with the plugin but you can also use an existing installation by providing TOPAZ_ENV_ACTIVATION (see below).

Important: you need to have conda (miniconda3 or anaconda3) pre-installed to use this program.

To check the installation you can run the plugin’s tests:

scipion tests topaz.tests.test_protocol_topaz.TestTopaz

Configuration variables

CONDA_ACTIVATION_CMD: If undefined, it will rely on conda command being in the PATH (not recommended), which can lead to execution problems mixing scipion python with conda ones. One example of this could can be seen below but depending on your conda version and shell you will need something different:

CONDA_ACTIVATION_CMD = eval “$(/extra/miniconda3/bin/conda shell.bash hook)”

TOPAZ_ENV_ACTIVATION (default = conda activate topaz-0.2.5): Command to activate the Topaz environment.

Supported versions

0.2.3, 0.2.4, 0.2.5

Protocols

• import training model

• picking

• training

References

• Bepler, T. et al. Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs. arXiv (2018).