Identify responding cells as outliers • stimgate

🧬 `stimgate`: Identify Responding Cells via Outlier Gating

stimgate is an R package for identifying cell populations that have responded to stimulation. It applies outlier gating functions to flow cytometry data, comparing unstimulated and stimulated tubes from the same sample to isolate stimulation-specific responses.

📦 Installation

# Install BiocManager and devtools if needed
if (!requireNamespace("BiocManager", quietly = TRUE)) {
  install.packages("BiocManager")
}
if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")
}

# Install all dependencies using Bioconductor and CRAN repos
devtools::install_github(
  "SATVILab/stimgate",
  repos = BiocManager::repositories(), dependencies = TRUE
)

🚀 Quick Start

library(stimgate)

# Get example dataset
example_data <- get_example_data()
gs <- flowWorkspace::load_gs(example_data$path_gs)

# Run the stimgate pipeline
path_project <- stimgate_gate(
  path_project = file.path(tempdir(), "stimgate_example"),
  .data = gs,
  batch_list = example_data$batch_list,
  marker = example_data$marker,
  pop_gate = "root"
)

# Get statistics for the identified gates
stats <- get_stats(path_project)

# Extract gate information
gates <- get_gate_tbl(path_project)

# Visualize results
stimgate_plot(
  ind = seq_len(2),
  .data = gs,
  path_project = path_project,
  marker = example_data$marker,
)

🔑 Features

Outlier-based gating: Identifies responding cells by comparing stimulated vs unstimulated samples
Batch processing: Handles multiple donors or experimental batches simultaneously
Background subtraction: Reduces false positives from baseline cytokine activity
Flexible gating: Supports various gating parameters and combinations
Comprehensive output: Generates statistics, gate tables, and visualization plots
FCS export: Write cytokine-positive cells to new FCS files for downstream analysis
Bioconductor compatibility: Designed for integration with flowCore, flowWorkspace, and CytoML

📖 Documentation

📘 Vignette: vignette("stimgate") - Getting started guide
🌐 Website: satvilab.github.io/stimgate
🔗 GitHub: github.com/SATVILab/stimgate
📦 Bioconductor: URL to be added upon release
🔧 Function reference: help(package = "stimgate")

Key Functions

stimgate_gate(): Main gating function to identify cytokine-positive cells
get_stats(): Generate comprehensive statistics from gating results
stimgate_plot(): Create bivariate hex and univariate density plots with gate overlays
get_gate_tbl(): Extract gate thresholds and parameters
stimgate_fcs_write(): Export cytokine-positive cells as FCS files

📌 Citation

citation("stimgate")

Rodo M. (2024). stimgate: Identify responding cells as outliers. R package version 0.3.1. https://github.com/SATVILab/stimgate

🤝 Contributing

We welcome bug reports, feature requests, and pull requests via GitHub Issues.

Development Guidelines

Before submitting changes, please ensure: - Run devtools::test() to verify all tests pass - Run devtools::document() to update documentation
- Run styler::style_pkg() for consistent code formatting - Run lintr::lint_package() to check for style violations

📄 License

This package is licensed under the MIT License. See LICENSE for details.

🧬 stimgate: Identify Responding Cells via Outlier Gating