GateLab

GateLab is a browser-based application for manually gating flow-cytometry and mass-cytometry (CyTOF) FCS files. It runs entirely in your web browser—no R installation or server-side analysis is required.

Launch GateLab in your browser →

No installation is required for the hosted app. Your FCS files and workspaces are processed locally in your browser and are not uploaded for analysis. GateLab can also be installed and run locally using the instructions below.

GateLab is a standalone reimplementation of GateLabR — it reuses GateLabR's vendored D3 plotting modules and reimplements its R analysis engine in TypeScript, so gating runs entirely in the browser with no R backend.

GateLab in action

GateLab or GateLabR?

GateLab and GateLabR share the same gating model and interactive plotting approach. Choose the version that best matches where your data already lives:

	GateLab	GateLabR
Runs in	A local web browser	R / Shiny
Best starting point	FCS files	A SingleCellExperiment (or FCS files)
Workspace	Self-contained .gatelab bundle	Gating metadata stored inside the SCE
Downstream hand-off	FCS, Gating-ML, statistics and figures	Populations in colData, plus FCS, Gating-ML, statistics and figures
Install	Open the hosted app, or use Node.js + npm locally	R + Bioconductor dependencies

GateLab is a standalone TypeScript port for users who do not need an R environment. Its interactive plots reuse GateLabR's D3 modules, while its analysis engine independently implements FCS parsing, logicle/arcsinh transforms, compensation, gate membership, population evaluation, statistics, Gating-ML 2.0 import/export and FCS export. These low-level operations are covered by unit tests and cross-language fidelity fixtures derived from GateLabR.

Using GateLab

GateLab runs entirely in a modern web browser, either from the hosted app or from a local installation. Chrome or Microsoft Edge are recommended for the best file open and save experience.

Features

• Multi-sample workspace with a shared gating tree across freely added or removed FCS files, with overlay / comparison across samples.
• Interactive gating: rectangle / polygon / quadrant gates, drag-to-edit, positive AND population hierarchies, and a population tree with counts / %parent / %total.
• Tabs: Gating, Strategy (single + multi-population back-gating), Illustration, Statistics, Panel, Scales, Division profiler, Proportions, Metadata.
• Import / export Gating-ML 2.0 (GateLabR / Cytobank dialects); export populations as FCS; SVG / PDF figure export.
• Self-contained .gatelab workspace bundle (workspace + original FCS + Gating-ML), with open → edit → save-in-place and debounced autosave.

GateLab currently uses positive AND population logic. Gating-ML files containing NOT or OR populations, or gates whose channels cannot be matched to the loaded data, are rejected before import with the affected populations, gates, and channels named. This prevents partial imports from silently changing membership. Broader Boolean logic may be considered in a future update if there is user demand.

How GateLab compares with other tools

GateLab is designed for researchers who want to leave proprietary cytometry software without giving up a familiar manual-gating workflow. It runs locally in the browser, uses portable self-contained workspaces and exchanges gates through Gating-ML—without requiring R or a commercial desktop/cloud platform.

	GateLab	FlowJo	Cytobank	CytoExploreR / flowGate
Interface	Local browser app	Desktop GUI	Cloud GUI	R with interactive gating helpers
Cost / license	Free, MIT, open source	Commercial	Commercial	Free, open source
Workspace and data	Self-contained .gatelab bundle with FCS files and gates	.wsp workspace linked to local FCS; ACS can bundle both	Cloud experiment	GatingSet / R objects
Gate exchange	Gating-ML 2.0 import and export	.wsp / .wspt workspace formats	Gating-ML 2.0 import and export	flowWorkspace / CytoML ecosystem
R required	No	No	No	Yes
Processing location	Local browser	Local desktop	Cloud	Local R session
Best suited to	Open-source FCS gating with portable local workspaces	Established desktop cytometry workflows	Shared cloud-based experiments	Scriptable R / flowWorkspace pipelines

See the official documentation for FlowJo workspace and export formats, Cytobank Gating-ML exchange, and the Bioconductor flowGate package.

FlowJo is a trademark of Becton, Dickinson and Company. GateLab is an independent project and is not affiliated with or endorsed by BD or FlowJo.

Local installation

What you need

• A current Node.js LTS installation (which includes npm).
• A Chromium-based browser such as Google Chrome or Microsoft Edge. GateLab uses the browser's File System Access API for opening and saving workspaces.

Run GateLab locally

# Clone the repository and its GateLabR plotting-module submodule, then enter it.
git clone --recurse-submodules https://github.com/david-priest/GateLab.git
cd GateLab

# Install the JavaScript dependencies (needed only after cloning or when they change).
npm install

# Start GateLab.
npm run dev

If you already cloned GateLab without submodules, initialise them once before running npm install:

git submodule update --init --recursive

Open the local URL printed in the terminal (normally http://localhost:5173) in Chrome or Edge. Leave that terminal running while using the app; press Ctrl+C there when you are finished.

First workspace

1. Create a new workspace or open an existing .gatelab workspace.
2. Add one or more .fcs files.
3. Select a population and use the Gating tab to choose markers, inspect the plot, and draw rectangle, polygon, or quadrant gates.
4. Review population counts and percentages in the tree and Statistics tab. Use the other tabs to inspect strategy, panel, scales, proportions, and metadata.
5. Save the workspace as a .gatelab bundle to retain its FCS inputs and gating strategy. You can also export Gating-ML, statistics, figures, or gated populations as FCS as needed.

Development commands

npm run dev      # Vite development server (normally :5173)
npm test         # Vitest engine unit tests
npm run build    # Type-check and create a production build

Issues and feature requests

Found a bug or have an idea that would make GateLab more useful? Please open an issue with the details. Bug reports and feature requests are welcome.

License

MIT — see LICENSE. GateLab bundles GateLabR's MIT-licensed D3 modules (license retained at vendor/GateLabR/LICENSE) and d3.v7 (ISC, © Mike Bostock). Bundled third-party components and their licenses (including DOMPurify, MPL-2.0/Apache-2.0, via jsPDF) are listed in THIRD-PARTY-NOTICES.md.