viewer controls
This page describes how to visualize and interact with the core outputs of a G4X run using the G4X Viewer. It assumes that you have access to the viewer either through a local installation or via the hosted application at g4x-viewer.singulargenomics.com.
To begin exploring your data, first load your sample into the viewer. Each G4X sample output contains a /g4x_viewer/ directory, which is described in detail in the G4X Viewer output documentation.
The files contained within this directory vary slightly between transcript-only and multiomics experiments, but all supported output formats are compatible with the G4X Viewer.
Each file contributes a specific interactive layer to the visualization, enabling simultaneous exploration of transcripts, cell segmentation, protein, and fH&E images. The sections below provide detailed guidance for loading data, configuring display settings, and using the available analysis and filtering tools.
source files
Learn how to load G4X data into the viewer and manage layer visibility using the available layer controls.
on-screen controls
Learn how to use the viewer's on-screen tools, including ROI selection, screenshot capture, polygon management, and other interactive controls.
protein layer
Learn how to customize protein visualizations, including channel selection, color assignment, display ranges, channel isolation, and related settings.
fH&E layer
Learn how to load, display, and adjust the fH&E image layer.
transcript layer
Learn how to customize transcript visualization, including transcript display density, color settings, filtering options, and transcript-specific controls.
segmentation layer
Learn how to customize cell segmentation displays, adjust mask appearance, and apply cell-level filtering based on clustering, protein expression, transcript abundance, and other analysis outputs.
UMAP filter
Learn how to use the UMAP filtering tool to select and visualize cell populations based on their position within the UMAP embedding.
flow cytometry filter
Learn how to use the flow cytometry filtering tool to identify and visualize cell populations based on protein expression distributions.
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