Update README.md

README.md

@@ -1,61 +1,54 @@
 ---
 language:
-- en
+  - en
+license: other
 tags:
-- biology
-- ESM
-- language-model
-- protein
-- VEP
-pretty_name: EVOScore-2
-size_categories:
-- 100M<n<1B
-license: mit
+  - biology
+  - genomics
+  - medical
+  - bioinformatics
+  - variant-annotation
+  - clinical
+  - wgs
+  - wes
+pretty_name: SchemaBio Bundle
 ---
 
-# Proteome-wide VESM-3B Variant Effect Scores (MIT Clean Mirror)
+# 🧬 SchemaBio Bundle
 
-![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)
-![Commercial Status](https://img.shields.io/badge/Status-Commercial--Safe-brightgreen)
+## 📖 Overview 
+This dataset is a comprehensive, meticulously curated, one-stop annotation library designed for bioinformatics and genomic variant analysis (e.g., WES/WGS pipelines). It aggregates essential variant effect predictors, clinical databases, and genomic reference files into a unified repository, significantly reducing the time spent on data collection, format alignment, and preprocessing.
 
-## ⚠️ Compliance & Mirror Notice
 
-This repository is a **strict subset** of the original [ntranoslab/vesm_scores](https://huggingface.co/datasets/ntranoslab/vesm_scores). 
 
-To ensure commercial compliance and safety, all non-commercial components (VESM3, Sequence-only VESM3, and VESM++) have been **permanently removed** from this mirror. 
+## 🗂️ Included Data & Sources
 
-**This repository contains ONLY the `VESM_3B` predictions**, which are based on the ESM2-3B architecture and explicitly released under the MIT License.
+This repository includes data from the following categories:
+1. **Variant Effect Predictors & Scores:** AlphaMissense, EVOScore2, Pangolin.
+2. **Clinical & Population Frequencies:** gnomAD, CIViC, mskcc_hotspot.
+3. **Genomic References & Regions:** UCSC annotations (`cytoband`, `ncbiRefSeq.gtf`), Ensembl references (`GRCh38/37 FASTA`, `vep_cache`), ManeSelectBed.
 
----
-
-## Dataset Description
-
-This repository provides precomputed **proteome-wide (UniProtKB, hg19, and hg38) variant-effect prediction scores** using the **VESM_3B** model.
-
-### Included Model
-* **VESM_3B:** A protein language model based on **ESM2 (3B parameter)** architecture. 
 
-*(Note: The original VESM3 and VESM++ models based on ESM3 have been excluded from this repository).*
 
-For more scientific details, please refer to the original GitHub repo: https://github.com/ntranoslab/vesm
+## ⚖️ Licensing & Commercial Use
 
-## Files Included
-* `hg38_VESM_3B_scores.parquet.gzip`
-* `hg19_VESM_3B_scores.parquet.gzip`
-* `hg38_VESM_3B_scores.vcf.gz`
-* `hg19_VESM_3B_scores.vcf.gz`
-* *(And any other Uniprot/metadata files strictly related to VESM_3B)*
+**Great news: All underlying datasets included in this repository currently permit commercial use**, provided that users strictly adhere to their respective attribution and share-alike requirements.
 
-## Threshold Recommend
+Because this repository acts as an aggregator, **it does not fall under a single license**. You must comply with the individual licenses of the respective underlying data sources. The table below outlines the specific license for each component:
 
-| P_threshold     | <-11.6    |
-| --------------- | ----------- |
-| **B_threshold** | **>-8.5** |
+### 📊 Database Licenses Summary
 
-## License <a name="license"></a>
+| Database / Source | Version | Official License | Commercial Use | Redistribution | Key Requirements & Notes |
+| :--- | :--- | :--- | :--- | :--- | :--- |
+| [**AlphaMissense**](https://zenodo.org/records/10813168) | v3 | **CC BY 4.0** | ✅ Allowed | ✅ Allowed | Must attribute to DeepMind Technologies Limited. |
+| [**EVOScore2**](https://huggingface.co/datasets/pzweuj/EVOScore-2) | 20260128 | **MIT** | ✅ Allowed | ✅ Allowed | Must include the original copyright notice. |
+| [**Pangolin**](https://zenodo.org/records/15649338) | v1 | **CC BY 4.0** | ✅ Allowed | ✅ Allowed | Must provide proper attribution. |
+| [**ManeSelectBed**](https://github.com/pzweuj/ManeSelectBed) | v49 | **MIT** | ✅ Allowed | ✅ Allowed | Must include the original copyright notice. |
+| [**mskcc_hotspot**](https://www.cancerhotspots.org/) | v2 | **ODbL** | ✅ Allowed | ✅ Allowed | **Share-Alike:** If you modify/adapt this database, the derivative must also be ODbL. |
+| [**CIViC**](https://civicdb.org/welcome) | 20260301 | **CC0 1.0** | ✅ Allowed | ✅ Allowed | Public Domain. No restrictions. |
+| [**gnomAD**](https://gnomad.broadinstitute.org/) | v4.1 | **Unrestricted** | ✅ Allowed | ✅ Allowed | Broad Institute claims no restrictions on use. |
+| [**UCSC Data**](https://hgdownload.soe.ucsc.edu/goldenPath) | / | **Public Domain** | ✅ Allowed | ✅ Allowed | Publicly funded data, free for all uses. |
+| [**Ensembl Data**](https://ftp.ensembl.org/pub/release-115/) | release 115 | **Unrestricted** | ✅ Allowed | ✅ Allowed | EMBL-EBI places no restrictions on use or redistribution. |
 
-The data provided in this repository is distributed under the **MIT License**.
+*Disclaimer: The creator of this combined dataset claims no ownership over the original source data. Users are solely responsible for ensuring their downstream use complies with the original data providers' terms.*
 
-> **Attribution:**
-> This dataset is a mirror of the VESM_3B predictions generated by Ntranos Lab.
-> While the original repository contained mixed licenses, the content hosted here is exclusively sourced from the MIT-licensed portion.