Data preparation
February 2, 2023 · View on GitHub
Datasets download
Here are all published dataset used in our paper.
| Index | Paper | Species | Tissue | Technology | Resolution | Cells/Spots | Genes | Download |
|---|---|---|---|---|---|---|---|---|
| 1 | Chen et al. | Mouse | Whole embryo | Stereo-seq | 0.2μm | 5000-100,000 | >20,000 | website |
| 2 | Lohoff et al. | Mouse | Whole embryo | seqFISH | subcellular | ~10,000 | 351 | website |
| 3 | Deng et al. | Mouse | Whole embryo | spatial-ATAC-seq | 20μm | 2099 | >20,000 | website |
| 4 | Jeffrey et al. | Mouse | Brain(hypothalamic preoptic) | MERFISH | subcellular | ~6,500 | 151 | website |
| 5 | Kristen et al. | Human | Brain(dorsolateral prefrontal cortex, DLPFC) | 10x Visium | 50μm | ~3500 | >20,000 | website |
| 6 | Amanda et al. | Human | Breast cancer | 10x Visium | 50μm | ~3500 | >20,000 | website |
| 7 | Amanda et al. | Human | Breast cancer | 10x Xenium | subcellular | > 140,000 | 311 | website |
Data preprocessing
We do some necessary pre-processing on some of them, you can repeat them by:
- For Stereo-seq, please follow the
./Stereo_process.ipynbto do pre-processing. - For spatial-ATAC-seq, we filter out the spots which not locate in tissue as authors did.