LabKick Flow
Describe the gating strategy and it lays the hierarchy onto your real plots. Batch across a plate is the default, and gates adapt where the population moves.
Top features
- Gating is describable
“Gate live singlets, then CD3+, then split CD4 vs CD8” draws the whole hierarchy onto the actual plots.
- Gates are proposed, never silent
You inspect and nudge before anything is applied. Nothing is gated behind your back.
- Batch that adapts per sample
Apply a strategy across 96 samples; gates shift where the population shifts, and the samples it is unsure about get flagged rather than mis-cut.
- Compensation handled up front
It reads the panel, applies compensation and flags spillover, with spectral unmixing where relevant, instead of you hunting a matrix by hand.
- It leads with the answer
“CD4+ went from 12% to 31% between control and treated”, populations and stats as a result, not a plot you then have to quantify.
- Straight into Stats
Populations flow to LabKick Stats for the test and the publication figure.
Everything in Flow
- .fcs ingest
- Dot plots
- Contour plots
- Histograms
- Pseudocolor plots
- Manual gate drawing
- Gating hierarchy editing
- Derived parameters
- Compensation matrices
- Spectral unmixing
- Spillover problems flagged
- Per-sample gate adaptation
- Per-sample uncertainty flags
- Batch application across plates
- Population statistics
- Overlays
- Panel and markers read from the experiment
- Hand-off into Stats
What changes
- The labor in FlowJo is mouse work: draw a gate, draw the next, build the hierarchy by hand, copy it across every sample, fix it where it does not fit. Those are the hours that go.
- Batch stops being an “apply template” chore that quietly mis-cuts the samples where the population moved.
- Every manual control survives. The floor drops to a sentence; the ceiling does not move.
Run it on your own data.
Flow is not sold on its own. One price gets you all nine tools, and the trial turns every one of them on.
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