Cell Type Annotation Using Large Language Models
Overview
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. (2026) doi:10.1038/s42003-026-10420-8.
Bug Fixes
- Disabled DeepSeek V4 thinking mode for cell-type annotation requests. DeepSeek V4 enables thinking by default, which could consume the 4,096-token response budget before producing final annotation text and lead to an invalid-response error.
- Increased the default R API request timeout from 30 to 120 seconds so slower non-streaming model responses, including DeepSeek V4 Pro annotations, are not aborted before completion. Set
options(mLLMCelltype.api_timeout = 300)to override the timeout when a longer response window is needed.
Maintenance
- Unified marker and tissue prompt preparation across plain and structured reasoning annotations so both modes stay consistent as prompt behavior evolves.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 65 (35 internal)includes a package overview page
- Examples that run
- 17%1 run in a plain check · 5 never run
- Exported functions with examples
- 20%
- Documented parameters
- 98%
- Return-value docs
- 43%
- Help pages citing references
- 0%
- mLLMCelltype: Overview and Quick Reference HTML
- Advanced Features & Case Studies HTML
- Consensus Annotation Principles HTML
- Consensus vs Single-Agent: A Methodology Comparison HTML
- Contributing Guide HTML
- Frequently Asked Questions HTML
- Getting Started with mLLMCelltype HTML
- Installation Guide HTML
- Introduction to mLLMCelltype HTML
- Usage Tutorial HTML
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Downloads
Repository
- PRs merged (all time)
- 97%
- Median days to close, 50 most recently updated closed issues
- 433
- Median days to close, 50 most recently updated closed PRs
- 0
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11 development-tooling and community-health practices detected across 6 families in the upstream repository
Checks run against github.com/cafferychen777/mllmcelltype on 2026-10-25.
Funding links: buymeacoffee.com, patreon.com
GitHub Pages site last deployed 2026-09-01 · The repository has a site deploy workflow
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This repository shows signs of AI coding tools.
- Claude Codefirst seen 2025-06-14Named in .gitignore: CLAUDE.mdCommits: at least 76 crediting it in the message
- Codexfirst seen 2026-08-18Named in .gitignore: .codex
- Claude Opus 4.11 commit · Aug 2025
- Claude Opus 4.61 commit · Jun 2026
- Claude Opus 4.81 commit · Jul 2026
Dependencies
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- 2.0.8Latest
- unarchivedReturned to CRAN2026-07-21
- 2.0.7
- archivedRemoved from CRAN2026-06-29issues were not corrected in time
- 2.0.5
- RR 4.6.0 released · 2026-04-24
- 2.0.02026-02-08 · diff ↗ ·
removed 1 export
QwenProcessoradded 3 exports
.qwen_endpoint_cache, mllmcelltype_cache_dir, mllmcelltype_clear_cache - 1.3.22025-09-02
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-09-02
- Total releases
- 5 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 538 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("mLLMCelltype")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1038/s42003-026-10420-8.
The repository also keeps a CITATION.cff.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.