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mLLMCelltype (version 2.0.0)

Cell Type Annotation Using Large Language Models

Description

Automated cell type annotation for single-cell RNA sequencing data using consensus predictions from multiple large language models. Integrates with Seurat objects and provides uncertainty quantification for annotations. Supports various LLM providers including OpenAI, Anthropic, and Google. For details see Yang et al. (2025) .

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Version

Install

install.packages('mLLMCelltype')

Monthly Downloads

164

Version

2.0.0

License

MIT + file LICENSE

Maintainer

Chen Yang

Last Published

February 8th, 2026

Functions in mLLMCelltype (2.0.0)

OpenAIProcessor

OpenAI API Processor
MinimaxProcessor

Minimax API Processor
AnthropicProcessor

Anthropic API Processor
BaseAPIProcessor

Base API Processor Class
configure_logger

Set global logger configuration
compare_model_predictions

Compare predictions from different models
ZhipuProcessor

Zhipu API Processor
combine_results

Combine results from all phases of consensus annotation
UnifiedLogger

Unified Logger for mLLMCelltype Package
check_consensus

Check if consensus is reached among models
clean_annotation

Clean annotation text by removing prefixes and extra whitespace
get_initial_predictions

Get initial predictions from all models
.onLoad

Package load message
.qwen_endpoint_cache

Qwen API Processor
annotate_cell_types

Cell Type Annotation with Multi-LLM Framework
get_logger

Get the global logger instance
calculate_simple_consensus

Calculate simple consensus without LLM
create_standardization_prompt

Create prompt for standardizing cell type names
create_initial_discussion_prompt

Create prompt for the initial round of discussion
extract_labeled_value

Extract numeric value from line containing a label
execute_consensus_check

Execute consensus check with retry logic
create_annotation_prompt

Create prompt for cell type annotation
process_controversial_clusters

Process controversial clusters through discussion
find_majority_prediction

Find majority prediction from response lines
process_custom

Process request using custom provider
facilitate_cluster_discussion

Facilitate discussion for a controversial cluster
filter_valid_responses

Filter out error responses from model round responses
custom_providers

Custom model manager for mLLMCelltype
get_provider

Determine provider from model name
get_model_response

Get response from a specific model
normalize_cluster_gene_list

Prompt templates for mLLMCelltype
create_consensus_check_prompt

Create prompt for checking consensus among model predictions
parse_consensus_response

Parse consensus response from model
prepare_models_list

Prepare list of models to try for consensus checking
mllmcelltype_clear_cache

Clear mLLMCelltype cache
parse_text_predictions

Parse text-format model predictions into a named list
create_discussion_prompt

Create prompt for additional discussion rounds
process_openai

Process request using OpenAI models
.onAttach

Package startup message
process_openrouter

Process request using OpenRouter models
register_custom_provider

Register a custom LLM provider
identify_controversial_clusters

Identify controversial clusters based on consensus analysis
resolve_provider_base_url

URL Utilities for Base URL Resolution
normalize_annotation

Normalize annotation for comparison
get_api_key

Utility functions for API key management
mLLMCelltype-package

mLLMCelltype: Cell Type Annotation Using Large Language Models
mllmcelltype_cache_dir

Get mLLMCelltype cache location
process_gemini

Process request using Gemini models
process_deepseek

Process request using DeepSeek models
initialize_logger

Reinitialize global logger with a specific directory
list_custom_models

Get list of registered custom models
interactive_consensus_annotation

Interactive consensus building for cell type annotation
process_qwen

Process request using Qwen models
parse_flexible_format

Parse flexible format consensus response
parse_standard_format

Parse standard 4-line consensus response format
list_custom_providers

Get list of registered custom providers
logging_functions

Convenience functions for logging
print_consensus_summary

Print summary of consensus results
process_minimax

Process request using MiniMax models
process_grok

Process request using Grok models
process_anthropic

Process request using Anthropic models
process_stepfun

Process request using StepFun models
select_best_prediction

Select the best prediction from consensus results
process_zhipu

Process request using Zhipu models
standardize_cell_type_names

Standardize cell type names using a language model
register_custom_model

Register a custom model for a provider
OpenRouterProcessor

OpenRouter API Processor
DeepSeekProcessor

DeepSeek API Processor
GeminiProcessor

Gemini API Processor
StepFunProcessor

StepFun API Processor
GrokProcessor

Grok API Processor
CacheManager

Cache Manager Class