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Introduction

The following sections document the usage of the steinbock command-line interface (CLI).

Prerequisites

From this point onwards, it is assumed that the steinbock command alias was configured correctly. To make efficient use of the steinbock Docker container, basic command line skills are absolutely required. Furthermore, understanding key concepts of containerization using Docker may be helpful in resolving issues.

Trying it out

To try out steinbock, the IMC mock dataset can be used as follows:

  1. Copy the raw directory to your steinbock data/working directory
  2. Place the panel.csv into the raw directory in your steinbock data/working directory
  3. Continue with Imaging Mass Cytometry (IMC) preprocessing and subsequent steps

Note

Existing Ilastik training data (Ilastik pixel classification project, Ilastik crops) can be used for testing the classification step.

Getting help

At any time, use the --help option to show help about a steinbock command, e.g.:

> steinbock --help

Usage: steinbock [OPTIONS] COMMAND [ARGS]...

Options:
--version  Show the version and exit.
--help     Show this message and exit.

Commands:
preprocess  Extract and preprocess images from raw data
classify    Perform pixel classification to extract probabilities
segment     Perform image segmentation to create object masks
measure     Extract object data from segmented images
export      Export data to third-party formats
utils       Various utilities and tools
view        View image using napari GUI
apps        Third-party applications

Directory structure

Unless specified otherwise, all steinbock commands adhere to the default directory structure.

For bug reports or further help, please do not hesitate to reach out via GitHub Issues/Discussions.