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README.md

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+---
+license: other
+#User-Defined Tags
+tags:
+  - single cell
+  - ST&SE
+language:
+  - en
+  - zh
+---
+<p align="center">
+  <strong>
+    <span style="font-size: 30px;">State Dataset</span>
+  </strong>
+</p>
+
+## Dataset Description
+
+`State_dataset` is a collection of datasets used for State single-cell expression modeling and perturbation prediction tasks. It comprises four data categories: Parse, Tahoe, Replogle-Nadig, and SE-167M-Human. The primary data is in AnnData/H5AD format, accompanied by gene embeddings (PyTorch `.pt`), dataset split configurations (TOML), and upstream license files.
+
+## Supported Tasks
+
+This repository corresponds to the experiment configurations in the `State` directory:
+`ST-HVG-Parse` and `ST-SE-Parse` use Parse data for few-shot/zero-shot splits by cell type or donor; `ST-HVG-Tahoe` uses Tahoe data for generalization evaluation; Replogle data is used for perturbation validation; and `SE-600M/config.yaml` describes the organization of large-scale cellxgene/Tahoe training data and gene embeddings.
+
+## Data Format and Structure
+
+The following sizes are based on file statistics from the current directory. File sizes may vary between data versions:
+
+| Subset | Main Files | Current File Size |
+|---|---|---:|
+| Parse | `parse_concat_full.h5ad` | Approximately 342.3 GiB |
+| Replogle-Nadig | 5 `.h5ad` files | Approximately 49.3 GiB |
+| Tahoe smoke | `c36.h5ad`, `c39.h5ad`, `c44.h5ad` | Approximately 5.0 GiB |
+| SE-167M-Human smoke | 1 `.pt` file + 4 `.h5ad` files | Approximately 607 MiB |
+
+H5AD files can be read with `scanpy`/`anndata`, while PT files can be read with PyTorch. The data paths in the configuration files are examples for the runtime environment. After migrating the data to a local environment, update the paths in the `State` configurations to the actual mount paths.
+
+## How to Use the Dataset
+
+After mounting this directory in the runtime environment, update the data path in the corresponding TOML file to the actual path. For example:
+
+```toml
+[datasets]
+parse = "/path/to/State_dataset/State-Parse-Filtered"
+```
+
+Read an H5AD file:
+
+```python
+import anndata as ad
+
+adata = ad.read_h5ad("State-Parse-Filtered/parse_concat_full.h5ad", backed="r")
+print(adata)
+```
+
+### Sharded Archives
+
+Because the complete directory is approximately 401 GiB, it has been split into multiple Zstandard-compressed shards of 90 GiB (binary) each. The shards are consecutive parts of the same compressed stream and cannot be decompressed independently; they must first be concatenated in order:
+
+```bash
+cat State_dataset.tar.zst.part-* > State_dataset.tar.zst
+zstd -d State_dataset.tar.zst -c | tar -xf -
+```
+
+Alternatively, stream the decompression directly without materializing the merged file:
+
+```bash
+cat State_dataset.tar.zst.part-* | zstd -d -c | tar -xf -
+```
+
+For shard filenames, actual sizes, and SHA256 checksums, refer to `State_dataset.tar.zst.sha256`, which was generated in the same directory.
+
+## Official OneScience Information
+
+| Platform | OneScience Main Repository | Skills Repository |
+|---|---|---|
+| Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
+| GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
+
+## Citation and License
+
+- Parse data source: Parse Biosciences, “Performance of Evercode WT v3 in Human Immune Cells (PBMCs)”; see `State-Parse-Filtered/README.md` and `CC-NC-4.0-License.txt`.
+- For Replogle-Nadig, Tahoe, and SE-167M-Human data, comply with the licenses, citation requirements, and usage restrictions of the respective upstream datasets.
+- This README only describes the current directory structure and does not alter the copyright or license terms of any upstream data.

README_zh.md

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+---
+license: other
+#用户自定义标签
+tags:
+  - single cell
+  - ST&SE
+language:
+  - en
+  - zh
+---
+<p align="center">
+  <strong>
+    <span style="font-size: 30px;">State Dataset</span>
+  </strong>
+</p>
+
+## 数据集描述
+
+`State_dataset` 是 State 单细胞表达建模与扰动预测任务使用的数据集合，包含 Parse、Tahoe、Replogle-Nadig 和 SE-167M-Human 四类数据。数据主体采用 AnnData/H5AD 格式，另包含基因 embedding（PyTorch `.pt`）、数据集切分配置（TOML）和上游许可证文件。
+
+## 数据集支持的任务
+
+该仓库与 `State` 目录中的实验配置对应：
+`ST-HVG-Parse` 和 `ST-SE-Parse` 使用 Parse 数据进行细胞类型或供体的 few-shot/zero-shot 切分；`ST-HVG-Tahoe` 使用 Tahoe 数据进行泛化评测；Replogle 数据用于扰动验证；`SE-600M/config.yaml` 描述了大规模 cellxgene/Tahoe 训练数据和基因 embedding 的组织方式。
+
+## 数据的格式和结构
+
+以下规模由当前目录文件统计得到，文件大小可能随数据版本变化：
+
+| 子集 | 主要文件 | 当前文件大小 |
+|---|---|---:|
+| Parse | `parse_concat_full.h5ad` | 约 342.3 GiB |
+| Replogle-Nadig | 5 个 `.h5ad` | 约 49.3 GiB |
+| Tahoe smoke | `c36.h5ad`、`c39.h5ad`、`c44.h5ad` | 约 5.0 GiB |
+| SE-167M-Human smoke | 1 个 `.pt` + 4 个 `.h5ad` | 约 607 MiB |
+
+H5AD 文件可使用 `scanpy`/`anndata` 读取，PT 文件可使用 PyTorch 读取。配置文件中的数据路径是运行环境示例路径，迁移到本地后需要把 `State` 配置中的路径改为实际挂载路径。
+
+## 数据集使用方式
+
+将本目录挂载到运行环境后，在对应 TOML 中把数据路径修改为实际路径。例如：
+
+```toml
+[datasets]
+parse = "/path/to/State_dataset/State-Parse-Filtered"
+```
+
+读取 H5AD：
+
+```python
+import anndata as ad
+
+adata = ad.read_h5ad("State-Parse-Filtered/parse_concat_full.h5ad", backed="r")
+print(adata)
+```
+
+### 分片压缩文件
+
+由于完整目录约 401 GiB，已按 90 GiB（二进制）切分为多个 Zstandard 压缩分片。分片是同一个压缩流的连续部分，不能单独解压；需要先按顺序合并：
+
+```bash
+cat State_dataset.tar.zst.part-* > State_dataset.tar.zst
+zstd -d State_dataset.tar.zst -c | tar -xf -
+```
+
+也可以不落地合并文件，直接流式解压：
+
+```bash
+cat State_dataset.tar.zst.part-* | zstd -d -c | tar -xf -
+```
+
+分片文件名、实际大小和 SHA256 校验值请以同目录生成的 `State_dataset.tar.zst.sha256` 为准。
+
+## OneScience 官方信息
+
+| 平台 | OneScience 主仓库 | Skills 仓库 |
+|---|---|---|
+| Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
+| GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
+
+## 引用与许可证
+
+- Parse 数据来源：Parse Biosciences，《Performance of Evercode WT v3 in Human Immune Cells (PBMCs)》，详见 `State-Parse-Filtered/README.md` 和 `CC-NC-4.0-License.txt`。
+- Replogle-Nadig、Tahoe、SE-167M-Human 数据请遵循各上游数据集的许可证、引用和使用限制。
+- 本 README 仅说明当前目录结构，不改变任何上游数据的版权或许可证条款。

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