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These pages provide documentation, example workflows, and helper tools for analyzing, and post-processing data generated by the G4X spatial sequencer.


G4X-helpers


Post-processing tools and helper models for G4X-data

With G4X-helpers we provide an open-source toolkit for common post-processing tasks — such as applying custom segmentations or adding your own labels to the G4X-viewer. You can access its core features from the command-line interface (CLI) and additionally import it as a standalone Python package to interact with your data.

In this section, you can:

  • learn how to install G4X-helpers on your system
  • get started with using the command line interface (CLI)
  • find a description of its CLI features


G4X-viewer


Explore and visualize your G4X-data

The G4X-viewer is a Python-based, multi-purpose, interactive viewer specifically designed to help you explore your G4X-data. The G4X-viewer is accessible through our website or can be downloaded from GitHub as a standalone application and hosted locally.

In this section, you can:

  • find resources to learn how to navigate your data with the G4X-viewer


G4X-data


Reference documentation for G4X-output files

The G4X produces multi-modal output containing tables, images, arrays and annotated matrices for single-cell analysis. The files found in the output directory are compatible with popular Python libraries from the scverse ecosystem, like scanpy, rapids-singlecell, squidpy, and spatial-data, and, if you prefer working in R, can be easily imported into Seurat.

In this section, you will find:

  • details on the G4X-output files and their organization
  • guides on importing G4X-data into popular analysis tools in Python and R


G4X-tutorials


Get started analyzing your data

G4X Tutorials are a collection of example workflows that demonstrate how to analyze G4X-data using popular Python and R libraries. These tutorials cover a wide range of topics, from basic data import and visualization to advanced analysis techniques.

In this section, you can:

  • learn how to plot spatial tissue information from the G4X-data
  • generate novel nuclear or cytoplasmic segmentations with popular models


Support


Got feedback or ideas for additional tutorials or documentation?
drop us a note at care@singulargenomics.com.