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Doublet Detection - Usage Guide

Overview

Doublets are events where two or more cells pass through the laser simultaneously. They appear as false intermediate populations and must be removed before downstream analysis.

Prerequisites

# R/Bioconductor
BiocManager::install(c('flowCore', 'flowDensity'))

Quick Start

Tell your AI agent what you want to do:

  • "Remove doublets from my flow cytometry data"
  • "Gate singlets using FSC-A vs FSC-H"
  • "Identify doublets in my CyTOF data"

Example Prompts

Standard Doublet Removal

"Create a singlet gate using FSC-A vs FSC-H" "Remove doublets from all samples in my flowSet" "Show the doublet rate for each sample"

CyTOF Doublet Removal

"Gate singlets using DNA intercalator channels" "Remove doublets based on Event_length" "Create a combined doublet filter using DNA and Event_length"

Quality Assessment

"Show FSC-A vs FSC-H plots before and after singlet gating" "Calculate the percentage of doublets removed per sample" "Flag samples with unusually high doublet rates"

What the Agent Will Do

  1. Identify appropriate doublet detection channels (FSC-A/H for flow, DNA/Event_length for CyTOF)
  2. Create singlet gate based on pulse geometry or DNA content
  3. Apply gate to remove doublets
  4. Calculate doublet rates and generate QC plots
  5. Return cleaned data for downstream analysis

Tips

  • FSC-A vs FSC-H is the standard method for conventional flow
  • Singlets show linear A vs H relationship; doublets have higher A for given H
  • CyTOF: use DNA intercalator (Ir191/Ir193) or Event_length
  • Expect 1-5% doublets in PBMCs, higher in tissue digests
  • High doublet rates (>15%) indicate sample preparation issues

Detection Methods

Method Instrument Principle
FSC-A vs FSC-H Flow Pulse geometry (singlets are linear)
FSC-A vs FSC-W Flow Doublets have increased width
DNA content CyTOF Doublets have ~2x DNA signal
Event_length CyTOF Doublets have longer transit time

Expected Doublet Rates

Sample Type Expected Rate
PBMCs 1-5%
Cell lines 2-10%
Tissue digest 5-15%
Sorted cells <1%

References

  • flowAI: doi:10.1093/bioinformatics/btw191
  • flowDensity: doi:10.1093/bioinformatics/btu677