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VirBiCla-training

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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

Dataset Sources [optional]

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

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 when using this dataset or the associated model.