docs: update publication citation metadata

Author: cafferychen777

CITATION.cff

@@ -8,8 +8,8 @@ authors:
   - family-names: "Chen"
     given-names: "Jun"
 title: "mLLMCelltype: Multi-LLM consensus framework for cell type annotation"
-version: 2.0.3
-date-released: 2025-04-10
+version: 2.0.5
+date-released: 2026-05-11
 url: "https://github.com/cafferychen777/mLLMCelltype"
 repository-code: "https://github.com/cafferychen777/mLLMCelltype"
 license: MIT
@@ -33,9 +33,7 @@ preferred-citation:
   title: "Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data"
   journal: "Communications Biology"
   year: 2026
-  volume: 9
-  start: 779
   date-released: 2026-06-08
   doi: "10.1038/s42003-026-10420-8"
   url: "https://doi.org/10.1038/s42003-026-10420-8"
-  publisher: "Nature Publishing Group"
+  publisher: "Springer Nature"

R/NEWS.md

@@ -1,5 +1,10 @@
 # mLLMCelltype Changelog
 
+## Unreleased
+
+### Documentation
+* Updated paper citation metadata to the Communications Biology publication DOI.
+
 ## 2.0.5 (2026-05-11)
 
 ### Bug Fixes

R/_pkgdown.yml

@@ -177,18 +177,17 @@ home:
       
       <p>Yang, C., Zhang, X., & Chen, J. (2026).
       <em>Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data</em>.
-      Communications Biology, 9, 779. <a href="https://doi.org/10.1038/s42003-026-10420-8">doi:10.1038/s42003-026-10420-8</a>.</p>
+      Communications Biology. <a href="https://doi.org/10.1038/s42003-026-10420-8">doi:10.1038/s42003-026-10420-8</a>.</p>
 
       ```bibtex
       @article{yang2026llmconsensus,
         author = {Yang, Chen and Zhang, Xianyang and Chen, Jun},
         title = {Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data},
         journal = {Communications Biology},
         year = {2026},
-        volume = {9},
-        pages = {779},
         doi = {10.1038/s42003-026-10420-8},
-        publisher = {Nature Publishing Group}
+        url = {https://doi.org/10.1038/s42003-026-10420-8},
+        publisher = {Springer Nature}
       }
       ```
   title: "mLLMCelltype: Cell Type Annotation Using Multi-LLM Consensus"

R/index.md

@@ -26,6 +26,8 @@
 
 mLLMCelltype is an R package that leverages various large language models (LLMs) for automated cell type annotation in single-cell RNA sequencing data. The package implements a **multi-LLM consensus architecture** where multiple LLMs collaborate through structured deliberation that aims to improve annotation reliability by combining multiple model predictions.
 
+The mLLMCelltype paper was published online in *Communications Biology* on June 8, 2026.
+
 ### Key Features
 
 * **Multi-LLM Consensus Mechanism**: Combines predictions from multiple LLMs to reduce individual model biases
@@ -117,16 +119,15 @@ If you use mLLMCelltype in your research, please cite our paper:
   title = {Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data},
   journal = {Communications Biology},
   year = {2026},
-  volume = {9},
-  pages = {779},
   doi = {10.1038/s42003-026-10420-8},
-  publisher = {Nature Publishing Group}
+  url = {https://doi.org/10.1038/s42003-026-10420-8},
+  publisher = {Springer Nature}
 }
 ```
 
 You can also cite this in plain text format:
 
-Yang, C., Zhang, X., & Chen, J. (2026). Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data. *Communications Biology*, 9, 779. https://doi.org/10.1038/s42003-026-10420-8
+Yang, C., Zhang, X., & Chen, J. (2026). Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data. *Communications Biology*. https://doi.org/10.1038/s42003-026-10420-8
 
 ### Learn More
 

R/inst/CITATION

@@ -2,18 +2,19 @@ citHeader("To cite mLLMCelltype in publications use:")
 
 bibentry(
   bibtype  = "Article",
-  title    = "Large Language Model Consensus Substantially Improves the Cell Type Annotation Accuracy for scRNA-seq Data",
+  title    = "Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data",
   author   = c(person("Chen", "Yang"),
                person("Xianyang", "Zhang"),
                person("Jun", "Chen")),
-  journal  = "bioRxiv",
-  year     = "2025",
-  doi      = "10.1101/2025.04.10.647852",
-  publisher = "Cold Spring Harbor Laboratory",
+  journal  = "Communications Biology",
+  year     = "2026",
+  doi      = "10.1038/s42003-026-10420-8",
+  url      = "https://doi.org/10.1038/s42003-026-10420-8",
+  publisher = "Springer Nature",
   textVersion = paste(
-    "Yang, C., Zhang, X., & Chen, J. (2025).",
-    "Large Language Model Consensus Substantially Improves the Cell Type Annotation Accuracy for scRNA-seq Data.",
-    "bioRxiv.",
-    "doi:10.1101/2025.04.10.647852"
+    "Yang, C., Zhang, X., & Chen, J. (2026).",
+    "Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data.",
+    "Communications Biology.",
+    "https://doi.org/10.1038/s42003-026-10420-8"
   )
 )

R/man/mLLMCelltype-package.Rd

@@ -121,7 +121,7 @@ If you use mLLMCelltype in your research, please cite:
 
 ```
 Yang, C., Zhang, X., & Chen, J. (2026). Large language model consensus substantially
-improves the cell type annotation accuracy for scRNA-seq data. Communications Biology, 9, 779.
+improves the cell type annotation accuracy for scRNA-seq data. Communications Biology.
 https://doi.org/10.1038/s42003-026-10420-8
 ```
 

R/vignettes/introduction.Rmd

@@ -201,7 +201,7 @@ If you use mLLMCelltype in your research, please cite:
 
 ```
 Yang, C., Zhang, X., & Chen, J. (2026). Large language model consensus substantially
-improves the cell type annotation accuracy for scRNA-seq data. Communications Biology, 9, 779.
+improves the cell type annotation accuracy for scRNA-seq data. Communications Biology.
 https://doi.org/10.1038/s42003-026-10420-8
 ```
 

R/vignettes/version-history.Rmd

@@ -73,7 +73,7 @@ Consensus frameworks leverage multiple independent models:
 
 For benchmark results comparing the two approaches, see Yang et al. (2026):
 
-Yang, C., Zhang, X., & Chen, J. (2026). Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data. *Communications Biology*, 9, 779. https://doi.org/10.1038/s42003-026-10420-8
+Yang, C., Zhang, X., & Chen, J. (2026). Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data. *Communications Biology*. https://doi.org/10.1038/s42003-026-10420-8
 
 ## Cost and Resource Trade-offs
 

R/vignettes/vs-single-agent.Rmd

@@ -17,7 +17,7 @@ knitr::opts_chunk$set(
 
 # Why Choose Consensus? The Scientific Foundation of Multi-LLM Annotation
 
-Multi-LLM consensus can improve annotation accuracy by combining the strengths of diverse AI models while reducing the impact of individual model limitations (see Yang et al., 2025).
+Multi-LLM consensus can improve annotation accuracy by combining the strengths of diverse AI models while reducing the impact of individual model limitations (see Yang et al., 2026).
 
 ## The Challenge with Single-Model Approaches
 
@@ -72,7 +72,7 @@ Cell type annotation involves:
 
 For benchmark results, see Yang et al. (2026):
 
-Yang, C., Zhang, X., & Chen, J. (2026). Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data. *Communications Biology*, 9, 779. https://doi.org/10.1038/s42003-026-10420-8
+Yang, C., Zhang, X., & Chen, J. (2026). Large language model consensus substantially improves the cell type annotation accuracy for scRNA-seq data. *Communications Biology*. https://doi.org/10.1038/s42003-026-10420-8
 
 ## Cost Considerations