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[AAAI 2026] This is an official implementation for "Evidence-aware Integration and Domain Identification of Spatial Transcriptomics Data".

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# PREST

This is the official implementation for our paper:"[Evidence-aware Integration and Domain Identification of Spatial Transcriptomics Data](https://juweipku.github.io/files/26AAAI_PREST.pdf)" (**PREST**:  **PR**ototype-based **E**vidence-aware integration framework for **S**patial **T**ranscriptomics data)

---

## Overview

![Overview](https://raw.githubusercontent.com/wayc04/PREST/main/PREST.png)

## Experiments

Please replace the following `{dataset_name}` with the actual dataset name.

### Setup

```bash
conda create -n PREST python=3.8.20
conda activate PREST
pip install -r requirements.txt
```

### Data

**To generate DLPFC data:**

1.  Set the `datasets` variable in `generate_data_DLPFC.py` to your target slice number (e.g., `151507`)
2.  Execute the generation script:

```bash
python generate_data_{dataset_name}.py
```

#### For All Other Datasets

Direct execution (no configuration needed):

```bash
python generate_data_{dataset_name}.py
```

### Pretrain

```bash
python ./pretrain/ae/main.py --name {dataset_name} --lr 1e-3 --epoch 100
python ./pretrain/gae/main.py --name {dataset_name} --lr 1e-3 --epoch 100
python ./main.py --name {dataset_name} --lr 1e-3 --epoch 100 --mode ntrain
```

### Train

```bash
python ./main.py --name {dataset_name} --epoch 200
```

## Datasets

You can download the benchmark datasets from the links below:

+ DorsoLateral PreFrontal Cortex (DLPFC): [LieberInstitute/spatialLIBD: Code for the spatialLIBD R/Bioconductor package and shiny app](https://github.com/LieberInstitute/spatialLIBD)
+ Human Breast Cancer (HBC):  [Human Breast Cancer (Block A Section 1) - 10x Genomics](https://www.10xgenomics.com/datasets/human-breast-cancer-block-a-section-1-1-standard-1-1-0)
+ Mouse Anterior Brain (MBA):  [Mouse Brain Serial Section 1 (Sagittal-Anterior) - 10x Genomics](https://www.10xgenomics.com/datasets/mouse-brain-serial-section-1-sagittal-anterior-1-standard-1-1-0)

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