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flow-cytometry

Flow cytometry experimental design and analysis — panel design, compensation, gating, and QC.

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Overview

flow-cytometry covers multicolor flow cytometry from panel design to analyzed data: fluorochrome selection, compensation and controls, gating strategies, and the QC that keeps cytometry honest. Flow generates single-cell data on millions of cells in minutes — but panel-design errors and bad gating produce confident-looking wrong answers at the same speed.

When to use

  • Designing antibody panels: fluorochrome assignment, spillover minimization.
  • Controls: unstained, FMO, isotype, biological controls, viability dyes.
  • Compensation: setup, validation, when to use beads vs cells.
  • Gating: hierarchical strategies, doublet exclusion, dump channels.
  • Analysis: manual gating vs automated clustering (FlowSOM, UMAP).
  • Sorting: purity vs yield, sterile sort considerations.
  • Troubleshooting: high background, poor resolution, clogging.

Core concepts

  • Panel design. Assign bright fluorochromes to low-density antigens and dim ones to high-density markers; minimize spillover into critical channels (check the spillover matrix for your instrument); respect laser/filter configurations. Use panel-design tools (FluoroFinder, BD spectrum viewer) — don't design from memory. Include viability dye always (dead cells bind antibodies nonspecifically and ruin everything).
  • Spillover and compensation. Fluorescence bleeds across detectors; compensation mathematically corrects it using single-stain controls. Compensation must be calculated per experiment (tandem dyes degrade — lot-to-lot variation is real). Validate with N×N plots: properly compensated populations show no diagonal correlation.
  • Controls. Unstained (autofluorescence baseline); FMO (fluorescence-minus-one — defines gates where spillover spreading affects the positive/negative boundary; essential for every channel in multicolor panels); biological controls (known positive/negative populations); isotype controls are largely obsolete (they don't control what people think they do — FMOs replaced them).
  • Gating hierarchy. FSC/SSC (cells vs debris) → singlets (FSC-H vs FSC-A, doublets excluded — doublets create fake double-positives) → viable (viability dye negative) → dump channel (exclude unwanted lineages) → populations of interest. Gate on controls, apply to samples; back-gate to verify populations land where expected.
  • Spillover spreading error. Compensation corrects the mean but not the spread — dim populations adjacent to bright ones in spillover-receiving channels lose resolution. This is physics, not fixable post-hoc: it's why panel design matters more than analysis tricks.
  • Counting and quantitation. Use counting beads for absolute counts; report percentages with the parent gate defined (percent of what?). MFI comparisons need identical instrument settings and controls across runs — or calibration beads.
  • Automated analysis. Dimensionality reduction (UMAP/t-SNE) + clustering (FlowSOM, PhenoGraph) for high-parameter data. Validate clusters against manual gating; automated methods find structure but also noise — always sanity-check with known populations.
  • Sorting. Purity vs yield trade-off (purity mask settings); keep cells cold and fast; sterility for culture downstream; sort controls to verify post-sort purity and viability.

Practical workflow

  1. Design. Marker list → fluorochrome assignment (brightness-matched, spillover-checked) → include viability + dump; order antibodies with lead time.
  2. Titrate. Antibody titration per lot (saturating concentration with best signal:noise — more antibody is not better).
  3. Stain. Consistent protocol: Fc block, surface stain, viability dye timing, fix/perm for intracellular (fixation changes fluorochromes — validate).
  4. Controls. Unstained + FMOs + single-stain compensation controls (beads or cells) every run.
  5. Acquire. Consistent voltages (use application settings/CS&T beads); record enough events for rare populations (statistics: need ~100+ events in the rarest gate).
  6. Analyze. Compensation check (N×N) → gating hierarchy on controls → apply → back-gate → statistics with defined parent gates.
  7. Report. Panel table (clone, fluorochrome, vendor, lot), gating strategy figure, control summary, and FCS files archived.

Common pitfalls

  • No viability dye (dead-cell artifacts presented as populations).
  • No doublet exclusion (fake double-positives).
  • Missing FMOs (gates drawn where spillover spreading corrupts boundaries).
  • Tandem-dye degradation ignored (compensation from a fresh lot applied to old reagents).
  • Under-acquiring rare populations (20 events is not a population).
  • MFI compared across runs without calibration.
  • Manual gates drawn to produce the desired result (gate on controls, blinded).

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