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bio-flow-cytometry-doublet-detection

Maintainer FreedomIntelligence · Last updated April 1, 2026

Detect and remove doublets from flow and mass cytometry data. Covers FSC/SSC gating and computational doublet detection methods. Use when filtering out cell aggregates before clustering or quantitative analysis.

OpenClawNanoClawAnalysisReproductionbio-flow-cytometry-doublet-detection🧬 bioinformatics (gptomics bio-* suite)bioinformatics — immunoinformatics & flow cytometrydetect

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

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

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

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

R: flowCore rectangular gates on FSC-A vs FSC-H.
Remove doublets from my flow cytometry data" → Detect and filter out cell aggregates using FSC-A/FSC-H gating or computational methods before clustering or quantitative analysis. R: flowCore rectangular gates on FSC-A vs FSC-H.
fs <- read.flowSet(list.files('data/', pattern = '\\.fcs$', full.names = TRUE)).

Source Doc

Excerpt From SKILL.md

FSC-A vs FSC-H Gating (Standard Method)

library(flowCore)
library(ggcyto)

## Manual rectangular gate

singlet_gate <- rectangleGate(
    filterId = 'singlets',
    'FSC-A' = c(50000, 250000),
    'FSC-H' = c(50000, 250000)
)

## Or use polygon gate for diagonal

singlet_polygon <- polygonGate(
    filterId = 'singlets',
    .gate = data.frame(
        'FSC-A' = c(50000, 250000, 250000, 50000),
        'FSC-H' = c(40000, 200000, 260000, 60000)
    )
)