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bio-flow-cytometry-bead-normalization

Maintainer FreedomIntelligence · Last updated April 1, 2026

Bead-based normalization for CyTOF and high-parameter flow cytometry. Covers EQ bead normalization, signal drift correction, and batch normalization. Use when correcting instrument drift in CyTOF or harmonizing data across batches.

OpenClawNanoClawAnalysisReproductionbio-flow-cytometry-bead-normalization🧬 bioinformatics (gptomics bio-* suite)bioinformatics — immunoinformatics & flow cytometrybead

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-flow-cytometry-bead-normalization

Maintainer: FreedomIntelligence
License: MIT
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

R: CATALYST::normCytof() for EQ bead normalization.
Normalize my CyTOF data using beads" → Correct instrument signal drift over acquisition time using EQ calibration bead intensities for consistent measurements across runs. R: CATALYST::normCytof() for EQ bead normalization.
ff <- read.FCS('cytof_with_beads.fcs').

Source Doc

Excerpt From SKILL.md

CyTOF EQ Bead Normalization

Goal: Identify EQ normalization bead events in CyTOF data for signal calibration.

Approach: Score events by mean scaled intensity in known bead channels (Ce140, Eu151, Eu153, Ho165, Lu175) and threshold at the 99th percentile.

library(CATALYST)
library(flowCore)

## EQ beads contain known amounts of: Ce140, Eu151, Eu153, Ho165, Lu175

bead_channels <- c('Ce140Di', 'Eu151Di', 'Eu153Di', 'Ho165Di', 'Lu175Di')

## Identify bead events (high signal in bead channels)

bead_data <- exprs(ff)[, bead_channels]
bead_scores <- rowMeans(scale(bead_data))