| # TReconLM synthetic test sets | |
| This dataset contains the synthetic test sets used to evaluate TReconLM, a transformer-based model for trace reconstruction of noisy DNA sequences (see [our paper](https://arxiv.org/pdf/2507.12927)). | |
| The real-world datasets used for fine-tuning are available here: | |
| - [Microsoft Clustered Nanopore Reads](https://github.com/microsoft/clustered-nanopore-reads-dataset) | |
| - [Noisy DNA Dataset](https://figshare.com/s/cd611884b34a8c89f4b4) | |
| The corresponding test sets used in the paper can be reproduced using the preprocessing scripts in our GitHub repository under [`data/`](https://github.com/MLI-lab/TReconLM/tree/main/data). | |
| ### Files Included | |
| - **`ground_truth.txt`** | |
| Contains the original DNA sequences, one per line | |
| - **`reads.txt`** | |
| Contains the noisy traces (corrupted copies of the ground-truth sequences) | |
| - Each line is a single read | |
| - Clusters are separated by: `===============================` | |
| - The *i*-th cluster corresponds to the *i*-th line in `ground_truth.txt` | |
| - **`test_x.pt`** | |
| A PyTorch tensor containing tokenized and padded input sequences used as model input, formatted as: read1|read2|...|readN : ground_truth | |
| ## Usage | |
| Instructions for running inference using these datasets and our pretrained models are provided in the [`trace_reconstruction.ipynb`](https://github.com/MLI-lab/TReconLM/blob/main/trace_reconstruction.ipynb) notebook in our GitHub repository. |