Spaces:
Sleeping
Sleeping
File size: 7,465 Bytes
93818e9 05fdb87 93818e9 05fdb87 93818e9 05fdb87 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 |
---
title: Spatial Transcriptomics Viewer
emoji: 🧬
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.0.0
app_file: app.py
pinned: false
license: mit
---
# Spatial Transcriptomics Viewer
A web-based tool for visualizing spatial gene expression from AnnData (.h5ad) files.
## Features
- **Interactive Visualization**: Explore spatial gene expression with interactive Plotly plots
- **Memory Efficient**: Uses AnnData backed mode for handling large datasets
- **Flexible Input**: Load data from URLs (HuggingFace, Zenodo) or upload files
- **Single-Gene Queries**: Visualize expression of individual genes across spatial coordinates
- **Expression Statistics**: Get detailed statistics for each gene
- **Customizable**: Adjust point size, color scale, and transformations
## Quick Start
### Using the Public Demo
1. Visit the Space URL
2. Load your data:
- **URL**: Paste a link to your h5ad file
- **Upload**: Upload your h5ad file directly (< 2GB recommended)
3. Enter a gene name and visualize!
### For Heavy Usage: Duplicate This Space
For large files or frequent use, we recommend duplicating this Space to your account:
1. Click the **⋮** menu at the top right
2. Select **"Duplicate this Space"**
3. Choose your HuggingFace account
4. (Optional) Upgrade to persistent storage for better performance
**Benefits of Duplicating:**
- Independent computing resources
- No queueing with other users
- Private data processing
- Customizable settings
- Optional paid upgrades for more resources
## Data Requirements
Your h5ad file must contain:
- `adata.obsm['spatial']`: 2D spatial coordinates (N × 2 array)
- Gene expression data in `adata.X`
- Gene names in `adata.var_names`
**Supported formats:**
- Visium (10x Genomics)
- MERFISH
- seqFISH
- Any spatial transcriptomics data in AnnData format
## How It Works
### Architecture
```
User Input (URL/Upload)
↓
Load h5ad with backed='r' (memory efficient)
↓
Validate spatial coordinates
↓
Query single gene expression
↓
Plotly interactive visualization
```
### Memory Efficiency
This tool uses AnnData's **backed mode** (`backed='r'`), which means:
- Files are read from disk on-demand
- Only requested data is loaded into memory
- Can handle files much larger than available RAM
- Suitable for large-scale spatial transcriptomics datasets
## Technical Details
### Stack
- **Frontend**: Gradio 4.0+
- **Backend**: Python 3.9+
- **Data**: AnnData, scanpy
- **Visualization**: Plotly
- **Platform**: Hugging Face Spaces
### File Size Limits
**Public Space:**
- Recommended: < 2GB
- Maximum: ~10GB (may be slow)
**Duplicated Space (Free):**
- Recommended: < 5GB
- With persistent storage upgrade: 50GB+
### URL Sources
Supported domains for URL input:
- `huggingface.co` - HuggingFace Datasets
- `zenodo.org` - Zenodo repositories
- `s3.amazonaws.com` - S3 buckets
## Usage Examples
### Example 1: Visualize from HuggingFace Dataset
```python
# If you have a h5ad file in a HuggingFace dataset:
URL = "https://huggingface.co/datasets/{username}/{dataset}/resolve/main/data.h5ad"
# Paste this URL in the tool and load
# Then enter gene names like: "GAPDH", "ACTB", "MYC"
```
### Example 2: Prepare Your Own Data
```python
import scanpy as sc
import numpy as np
# Load your data
adata = sc.read_10x_h5("your_data.h5")
# Add spatial coordinates (if not already present)
# Example: load from spatial folder
spatial = sc.read_visium("path/to/spatial_folder")
adata.obsm['spatial'] = spatial.obsm['spatial']
# Save as h5ad
adata.write("your_spatial_data.h5ad")
# Upload to HuggingFace Dataset or use directly
```
## Privacy & Data Security
### Public Space
- Files are processed in **temporary storage**
- No permanent data retention
- Cleared after session ends
- Not suitable for sensitive data
### Duplicated Private Space
- Data stays in your account
- Full control over access
- Suitable for private research data
- Can delete anytime
## Limitations
- **No preprocessing**: Tool does not normalize, scale, or transform data
- **Read-only**: Cannot modify or save h5ad files
- **Single gene**: Visualize one gene at a time
- **2D spatial only**: Requires 2D coordinates in `obsm['spatial']`
## Troubleshooting
### "Spatial coordinates not found"
- Check that your h5ad contains `adata.obsm['spatial']`
- Ensure it's a 2D array (N × 2)
### "Gene not found"
- Check gene name spelling
- Use exact gene names from `adata.var_names`
- Tool will suggest similar gene names
### "File too large" or slow loading
- Try duplicating the Space for more resources
- Consider subsetting your data
- Use URL input instead of upload
### Memory errors
- Ensure backed mode is working (check file size limits)
- Duplicate Space for more RAM
- Consider downsampling your dataset
## Development
### Local Setup
```bash
# Clone the repository
git clone <repo_url>
cd spatial-viewer
# Install dependencies
pip install -r requirements.txt
# Run locally
python app.py
```
### Project Structure
```
spatial-viewer/
├── app.py # Main Gradio application
├── utils/
│ ├── __init__.py
│ ├── loader.py # H5ad loading with backed mode
│ ├── validator.py # AnnData validation
│ └── plot.py # Plotly visualization
├── data/
│ └── demo.h5ad # (Optional) Demo dataset
├── requirements.txt # Python dependencies
├── README.md # This file
└── .huggingface/
└── space_config.yaml # HF Space configuration
```
## Contributing
Contributions welcome! Areas for improvement:
- Multi-gene visualization
- Additional plot types
- Performance optimizations
- UI enhancements
- Documentation
## Citation
If you use this tool in your research, please cite:
```bibtex
@software{spatial_viewer,
title = {Spatial Transcriptomics Viewer},
author = {Your Name},
year = {2025},
url = {https://huggingface.co/spaces/...}
}
```
## License
MIT License - see LICENSE file for details
## Acknowledgments
- Built with [Gradio](https://gradio.app/)
- Uses [AnnData](https://anndata.readthedocs.io/) and [Scanpy](https://scanpy.readthedocs.io/)
- Hosted on [Hugging Face Spaces](https://huggingface.co/spaces)
---
## 中文说明
### 功能特点
这是一个基于网页的空间转录组基因表达可视化工具,支持 AnnData (.h5ad) 格式。
**主要特性:**
- 交互式可视化
- 内存高效(支持大文件)
- 灵活的输入方式(URL 或上传)
- 单基因表达查询
- 表达量统计分析
### 使用方法
1. **加载数据**:通过 URL 或上传 h5ad 文件
2. **输入基因名**:输入您想查看的基因
3. **可视化**:查看空间表达图和统计信息
### 大文件或高频使用
对于大型 h5ad 文件(>2GB)或频繁使用,建议 **复制此 Space** 到您的账户:
- 独立计算资源
- 无需排队
- 数据隐私保护
- 可选付费升级
### 数据要求
您的 h5ad 文件必须包含:
- `adata.obsm['spatial']`:空间坐标(N × 2)
- `adata.X`:基因表达数据
- `adata.var_names`:基因名称
支持 Visium、MERFISH、seqFISH 等格式。
### 技术原理
使用 AnnData 的 **backed 模式**(`backed='r'`):
- 按需从磁盘读取数据
- 内存占用最小化
- 可处理大于内存的文件
- 适合大规模空间转录组数据
---
**为空间转录组研究社区构建** 🧬
|