|
--- |
|
license: mit |
|
--- |
|
|
|
# Dataset Card for VirBiCla-training |
|
|
|
VirBiCla is a ML-based viral DNA detector designed for long-read sequencing metagenomics. |
|
|
|
This dataset is a support dataset for training the base ML model. |
|
|
|
## Dataset Details |
|
|
|
### Dataset Description |
|
|
|
- **Curated by:** [Astra Bertelli](https://astrabert.vercel.app/) |
|
- **License:** MIT License |
|
|
|
### Dataset Sources [optional] |
|
|
|
<!-- Provide the basic links for the dataset. --> |
|
|
|
- **Repository:** [GitHub repository for VirBiCla](https://github.com/AstraBert/VirBiCla) |
|
|
|
## Uses |
|
|
|
This dataset is intended as support for training the base VirBiCla model |
|
|
|
|
|
## Dataset Structure |
|
|
|
Dataset is a CSV file composed of 60.003 record sequences (coming from RefSeq 16S bacterial rRNA, 18S fungal rRNA, SSU eukaryotic rRNA and RefSeq viral genomes) evaluated on 13 features. |
|
|
|
Features are: |
|
|
|
- Domain |
|
- A, T, C and G proportion |
|
- Percentage of A, T, C and G homopolimeric regions |
|
- Gene density |
|
- Entropy |
|
- Effective Number of Codons (codon usage metrics) |
|
|
|
## Dataset Creation |
|
|
|
Find everything that is needed for Dataset creation on [VirBiCla website](https://astrabert.github.io/VirBiCla) |
|
|
|
## Bias, Risks, and Limitations |
|
|
|
The dataset is mainly directed towards amplicon-sequencing and long-read sequencing, which are the best use cases for VirBiCla. |
|
|
|
|
|
## Citation |
|
|
|
Please consider cite the author of this work (Astra Bertelli) and VirBiCla [GitHub repository](https://github.com/AstraBert/VirBiCla) when using this dataset or the associated model. |
|
|
