Revise README for clarity and additional information (#30)

Updated README.md to enhance content and formatting.

Author: parashardhapola

README.md

@@ -1,50 +1,130 @@
-# CyteTypeR
+<h1 align="left">CyteTypeR</h1>
+<h3 align="left">Automated, evidence-based cell type annotation for single-cell transcriptomics</h3>
 
-CyteTypeR is the R version of CyteType, a single‑cell RNA‑seq cluster annnotation using multi-agent workflow [CyteType](https://github.com/NygenAnalytics/CyteType). 
-Current version of this package interfaces with **Seurat objects** after clustering and characterize cell clusters through CyteType API.
+<p align="left">
+  <a href="https://raw.githubusercontent.com/NygenAnalytics/CyteType/refs/heads/master/LICENSE.md">
+    <img src="https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg" alt="License: CC BY-NC-SA 4.0">
+  </a>
+</p>
 
-**For AnnData .h5ad, check out the python client: [CyteType](https://github.com/NygenAnalytics/CyteType)**
+---
 
+> 🎉 **NEW:** [Preprint published November 7, 2025](https://www.biorxiv.org/content/10.1101/2025.11.06.686964v1) on bioRxiv  
+> 📅 **FREE Webinar:** [Register now](https://attendee.gotowebinar.com/register/1731194703386732893) — Learn CyteType from the developers
+
+---
+
+## Why CyteTypeR?
+
+Manual cell type annotation takes weeks and varies between experts. CyteTypeR delivers consistent, expert-level annotations in minutes using a multi-agent AI system where specialized agents collaborate on marker analysis, literature evidence, and Cell Ontology mapping.
+
+<img width="800" alt="CyteType Overview" src="https://github.com/user-attachments/assets/c4cc4f67-9c63-4590-9717-c2391b3e5faf" />
+
+- **Save weeks of manual curation** — Annotate entire datasets at expert level in minutes, not days
+- **Drop-in integration** — 3 lines of code, works with existing Scanpy/Seurat workflows
+- **No setup friction** — No API keys required; built-in LLM with optional custom configuration
+- **Standards-compliant output** — Automatic Cell Ontology term mapping (CL IDs)
+- **Comprehensive annotations** — Cell types, subtypes, activation states, confidence scores, and lineage
+- **Transparent and auditable** — Interactive HTML reports show evidence, reasoning, and confidence for every annotation
+
+**[See example report](https://prod.cytetype.nygen.io/report/6420a807-8bf3-4c33-8731-7617edfc2ad0?v=251124)**
+
+---
 
 ## Installation
+
 ``` R
 # Using devtools
 install.packages("devtools")
 
 # Install from GitHub
 library(devtools)
 install_github("NygenAnalytics/CyteTypeR")
-
 ```
 
-## Quick Start Example
-``` R
+## Quick Start
+
+```R
 # Load package
 library(CyteTypeR)
 
-prepped_data <- PrepareCyteTypeR(pbmc,
-         pbmc.markers,
-         n_top_genes = 10,
-         group_key = 'seurat_clusters',
-         aggregate_metadata = TRUE,
-         coordinates_key = "umap")
+prepped_data <- PrepareCyteTypeR(
+  pbmc,
+  pbmc.markers,
+  n_top_genes = 10,
+  group_key = 'seurat_clusters',
+  aggregate_metadata = TRUE,
+  coordinates_key = "umap"
+)
 
 metadata <- list(
   title = 'My scRNA-seq analysis of human pbmc',
   run_label = 'initial_analysis',
-  experiment_name = 'pbmc_human_samples_study')
+  experiment_name = 'pbmc_human_samples_study'
+)
+
+results <- CyteTypeR(
+  obj=pbmc,
+  prepped_data = prepped_data, 
+  study_context = "pbmc blood samples from humans", 
+  metadata = metadata
+)
+```
+
+> **Note:** No API keys required for default configuration. See [custom LLM configuration](docs/configurations.md#llm-configurations) for advanced options.
+
+**Using Scanpy/Anndata?** → [CyteType](https://github.com/NygenAnalytics/CyteType)
+
+---
+
+## Output Reports
 
-results <- CyteTypeR(obj=pbmc,
-                          prepped_data = prepped_data, 
-                          study_context = "pbmc blood samples from humans", 
-                          metadata = metadata
-                          )
+Each analysis generates an HTML report documenting annotation decisions, marker genes, confidence scores, and Cell Ontology mappings:
+
+<img width="1000" alt="CyteType Report Example" src="https://github.com/user-attachments/assets/9f0f4b36-2dd7-4cb8-93e3-ecda9c97a930" />
+
+**[View example report with embedded chat interface](https://prod.cytetype.nygen.io/report/6420a807-8bf3-4c33-8731-7617edfc2ad0?v=251124)**
+
+---
+
+## Benchmarks
+
+Validated across multiple datasets, tissues, and organisms. CyteType's agentic architecture consistently outperforms other methods across multiple LLMs:
+
+**📊 Performance:** 388% improvement over GPTCellType, 268% over CellTypist, 101% over SingleR
+
+<img width="500" alt="CyteType Benchmark Results" src="https://github.com/user-attachments/assets/a63cadc1-d8c5-4ac0-bba7-af36f9b3c46d" />
+
+**[Browse results from single-cell atlases →](docs/examples.md)**
+
+## Need Help?
+
+📖 [Configuration options](docs/configurations.md)
+💬 [Join Discord](https://discord.gg/V6QFM4AN) for support
+
+---
+
+## Citation
+
+If you use CyteTypeR in your research, please cite our preprint:
+
+```bibtex
+@article{cytetype2025,
+  title={Multi-agent AI enables evidence-based cell annotation in single-cell transcriptomics},
+  author={Gautam Ahuja, Alex Antill, Yi Su, Giovanni Marco Dall'Olio, Sukhitha Basnayake, Göran Karlsson, Parashar Dhapola},
+  journal={bioRxiv},
+  year={2025},
+  doi={10.1101/2025.11.06.686964},
+  url={https://www.biorxiv.org/content/10.1101/2025.11.06.686964v1}
+}
 ```
 
-## Documentations
-- [Get started](docs/get-started.md)
-- [Configurations](docs/configurations.md)
+---
 
 ## License
 
-Licensed under CC BY‑NC‑SA 4.0 — see: [LICENSE.md](LICENSE.md)
+CyteTypeR is free for academic and non-commercial research use under CC BY‑NC‑SA 4.0 — see [LICENSE.md](LICENSE.md)
+
+For commercial use, please contact us at [contact@nygen.io](mailto:contact@nygen.io)
+
+