Your FlowJo gates, reproduced on your own events. Then run at a scale the desktop can't.
FlowCyto imports your .wsp, re-derives every gate on your own events, and shows you the delta against FlowJo's own recorded numbers — so the match is something you check, not something we claim. Then it opens full spectral panels and whole plates in the browser, with no RAM ceiling and no downsampling.
start free · no dongle · no credit card
Your gates come with you — to within a few events.
Switching tools means betting that the new one lands populations where the old one did. So we make the bet checkable: import a FlowJo workspace and FlowCyto re-runs the gating hierarchy on your events, then reports every population side by side with FlowJo's own recorded counts and the delta.
- Logicle / biexponential transforms — vs published equations
- Spillover compensation matrices — exact import
- Polygon · quadrant gate geometry — vs GatingML 2.0
- FCS reading across 33 instruments — byte-faithful
The logicle transform we use is the published Parks–Moore–Roederer formulation, not a proprietary black box, so the math that places a cell is auditable, and reproducible on your machine or ours.
| Population | FlowJo | FlowCyto | Δ |
|---|---|---|---|
| Lymphocytes | 19,212 | 19,225 | 0.07% |
| Singlets | 18,689 | 18,702 | 0.07% |
| Singlets2 | 18,573 | 18,585 | 0.06% |
| NK1_1+ | 923 | 923 | 0.00% |
| NK cells | 312 | 312 | 0.00% |
| NK T cells | 535 | 535 | 0.00% |
| NK1_1- | 17,458 | 17,470 | 0.07% |
| B cells | 2,459 | 2,460 | 0.04% |
| T cells | 10,745 | 10,747 | 0.02% |
| ab T cells | 9,188 | 9,191 | 0.03% |
| CD4 T cells | 7,480 | 7,482 | 0.03% |
| CD8 T cells | 1,407 | 1,407 | 0.00% |
| DN T cells | 266 | 267 | 0.38% |
| DP T cells | 6 | 6 | 0.00% |
| gd T cells | 1,470 | 1,470 | 0.00% |
Built for the data the desktop chokes on
Full-fidelity scale and reproducibility-by-default, in the very first release, alongside the daily gating workflow you already know by heart.
Full panels, every event
Open a 30-color spectral panel or a whole 384-well run and gate on every event, not a 60k subsample. The data stays server-side in a columnar store; the browser holds only the view. Rare-event and MRD analysis never has to bias itself down to fit RAM.
Reproducible by default
Every gate, transform, and compensation edit commits to a versioned Analysis Spec. Restore any prior state in one click, or re-run months later for identical numbers. No manual bookkeeping, no "which version was the figure?"
Reads everything
FCS 2.0/3.0/3.1, Beckman LMD, CSV, TSV, Parquet, from Aurora, Symphony, Fortessa, CytoFLEX. $PnE log/linear, gain and voltage keywords, time parameter, spillover matrix: all preserved on import.
Browser-native
No dongle, no activation, no quote request. Sign in with SSO and you're gating in seconds, on any machine, shared with your lab, identical for everyone who opens it.
Separate the analysis from its execution
You edit a declarative Analysis Spec; a content-addressed engine executes it out-of-core over immutable, hashed inputs. Because the spec, the inputs, and the engine version are all pinned, the same analysis always produces the same numbers, and any value traces back to exactly what made it.
- Content-hashed, immutable raw inputs
- Linear version history with one-click restore
- Hover any value for its full lineage
- Re-run a months-old document for identical results
Identical on your laptop, a teammate's, CI, or an air-gapped on-prem deployment.