Installation Guide

Chen Yang

2026-02-07

Installation Guide

This guide provides detailed instructions for installing and configuring mLLMCelltype for cell type annotation in single-cell RNA sequencing data.

System Requirements

Before installing mLLMCelltype, ensure your system meets the following requirements:

Installing the R Package

Installation from GitHub (Development Version)

To install the latest development version from GitHub:

# Install devtools if not already installed
if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")
}

# Install mLLMCelltype development version
devtools::install_github("cafferychen777/mLLMCelltype", subdir = "R")

Installation from a Local Source

If you have downloaded the source code or need to install from a local copy:

# Assuming the package is in the current working directory
devtools::install_local("path/to/mLLMCelltype/R")

Dependencies

mLLMCelltype depends on several R packages that will be automatically installed during the installation process. The main dependencies include:

For visualization and integration with single-cell analysis workflows, the following packages are recommended but not required:

API Keys Setup

mLLMCelltype requires API keys to access different LLM providers. You will need to obtain API keys for at least one of the supported providers:

Obtaining API Keys

  1. OpenAI (GPT-4o/4.1)
    • Visit OpenAI Platform
    • Create an account or log in
    • Navigate to API keys section
    • Create a new API key
  2. Anthropic (Claude-3.7/3.5)
    • Visit Anthropic Console
    • Create an account or log in
    • Generate an API key
  3. Google (Gemini-2.0/2.5)
  4. Other Providers
    • Similar processes apply for DeepSeek, Qwen, Zhipu, MiniMax, Stepfun, and Grok
    • Visit their respective websites to obtain API keys

Setting Up API Keys

There are three ways to set up your API keys:

1. Environment Variables

Create a .env file in your project directory with your API keys:

# API Keys for different LLM models
OPENAI_API_KEY=your-openai-key
ANTHROPIC_API_KEY=your-anthropic-key
GEMINI_API_KEY=your-gemini-key
DEEPSEEK_API_KEY=your-deepseek-key
QWEN_API_KEY=your-qwen-key
ZHIPU_API_KEY=your-zhipu-key
STEPFUN_API_KEY=your-stepfun-key
MINIMAX_API_KEY=your-minimax-key
GROK_API_KEY=your-grok-key
OPENROUTER_API_KEY=your-openrouter-key

Then load the environment variables in your R script:

library(dotenv)
dotenv::load_dot_env()

2. Direct Specification in Function Calls

You can directly provide API keys in function calls:

library(mLLMCelltype)

results <- annotate_cell_types(
  input = your_marker_data,
  tissue_name = "human PBMC",
  model = "claude-sonnet-4-5-20250929",
  api_key = "your-anthropic-key",
  top_gene_count = 10
)

3. R Environment Variables

Set API keys as R environment variables:

Sys.setenv(OPENAI_API_KEY = "your-openai-key")
Sys.setenv(ANTHROPIC_API_KEY = "your-anthropic-key")
# Set other API keys as needed

Verifying Installation

To verify that mLLMCelltype is installed correctly and API keys are set up properly:

library(mLLMCelltype)

# Check if the package is loaded correctly
packageVersion("mLLMCelltype")

# Verify API key setup for a specific provider
api_key <- get_api_key("anthropic")
if (!is.null(api_key) && api_key != "") {
  cat("Anthropic API key is set up correctly\n")
} else {
  cat("Anthropic API key is not set up\n")
}

Common Installation Issues

Package Installation Failures

If you encounter issues during installation:

  1. Check R version: Ensure you’re using R 4.0.0 or higher
  2. Update devtools: Run install.packages("devtools") to ensure you have the latest version
  3. Check dependencies: Some dependencies might require system libraries on Linux

API Connection Issues

If you encounter issues connecting to LLM APIs:

  1. Verify API keys: Ensure your API keys are correct and have not expired
  2. Check internet connection: Ensure you have a stable internet connection
  3. Proxy settings: If you’re behind a proxy, configure R to use your proxy settings
# Example of setting proxy for httr
httr::set_config(httr::use_proxy(url = "proxy_url", port = proxy_port))

Memory Limitations

For large datasets, you might encounter memory issues:

  1. Increase R memory limit: Use memory.limit(size = 16000) on Windows to increase available memory
  2. Process data in batches: Consider processing large datasets in smaller batches

Next Steps

Now that you have installed mLLMCelltype, you can proceed to:

If you encounter any issues not covered in this guide, please open an issue on our GitHub repository.