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mLLMCelltype

2.0.8Package record

Cell Type Annotation Using Large Language Models

0packages depend
3.1Kdownloads / year
82.7%test coverage
13/13flavors OK

Overview

About

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.

Changes in 2.0.8

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

CRAN checks
13OK
Slowest check: 2.5 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 2.0.8
READMENoVignettesYes · 12 · dynamicNEWSYes · 100% structured · mentions 2.0.8Citation fileYes · cites a publicationWebsiteYes
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%

Downloads

3.1K
CRAN downloads in the past year
Rank #13,945 · ~8/day · ~255/mo
Daily download trend is not available in this view yet.
24930 days
85290 days
3.1K1 year
Compare downloads with other packages →
Also on86 r2u4 autocran

Repository

661Stars
59Forks
5Open issues
4Open PRs
10Releases
525Commits
3Commit identities
bioinformaticscell-type-annotationconsensus-algorithmlarge-language-modelsllmscanpyseuratsingle-cell
License file reads as MIT · 525 commits · Last activity 2026-09-24 · -0.2% stars, 30d · Discussions: 2 posts
Responsiveness
How these are sampled
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

Stars over time

2026-07-21 · 6522026-10-08 · 661
PracticesBeta

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.

Continuous integration (1)
GitHub Actions
Governance and community (5)
Code of conductContributing guideIssue templatesPR templateFunding

Funding links: buymeacoffee.com, patreon.com

Docs source (2)

GitHub Pages site last deployed 2026-09-01 · The repository has a site deploy workflow

Research and citation (1)
CITATION.cff
Show all practicesHide 2 practices
Automation and maintenance (1)
Dependabot
Git structural (1)
.gitattributes
How this is detected·Detection ruleset v4 (2026-10-20)
AI coding toolsBeta

This repository shows signs of AI coding tools.

  • Claude Codefirst seen 2025-06-14
    Named in .gitignore: CLAUDE.md
    Commits: at least 76 crediting it in the message
  • Codexfirst seen 2026-08-18
    Named in .gitignore: .codex
Shared conventions any agent may read, so they name no particular tool.
Seen in the repository: AGENTS.md
Models named in its commits
  • Claude Opus 4.11 commit · Aug 2025
  • Claude Opus 4.61 commit · Jun 2026
  • Claude Opus 4.81 commit · Jul 2026
Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies
8 external dependencies (excludes base and recommended)

Installing mLLMCelltype adds 9 packages (7 with compiled code, 3.2 MB of source tarballs). Heaviest: openssl 1.1 MB, jsonlite 1.0 MB, curl 714 KB.

Depends (0)
none
Imports (7)
httrjsonliteR6digeststatstoolsutils
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (1)
Author, Maintainer since 1.3.2 (2025), Copyright holder
Releases (5)

Pick two releases to compare their code metrics.

  • 2.0.8Latest
    record
    2026-09-01 · current release · diff ↗
  • unarchivedReturned to CRAN
    2026-07-21
  • 2.0.7
    record
    2026-07-21 · diff ↗ ·
    added 2 exports
    KimiProcessor, create_reasoning_annotation_prompt
  • archivedRemoved from CRAN
    2026-06-29
    issues were not corrected in time
  • 2.0.5
    record
    2026-05-11 · diff ↗ ·
    removed 1 export
    .qwen_endpoint_cache
    added 1 export
    QwenProcessor
  • R
    R 4.6.0 released · 2026-04-24
  • 2.0.0
    record
    2026-02-08 · diff ↗ ·
    removed 1 export
    QwenProcessor
    added 3 exports
    .qwen_endpoint_cache, mllmcelltype_cache_dir, mllmcelltype_clear_cache
  • 1.3.2
    record
    2025-09-02
  • R
    R 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.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for mLLMCelltype version 2.0.8 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

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.

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