Datasets:
Ahmed Moustafa
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Parent(s):
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Cleaning up
Browse files- README.md +28 -11
- gg_2024_09_testing.fna.gz +2 -2
- gg_2024_09_testing.tsv.gz +2 -2
- gg_2024_09_testing_ids.txt +0 -0
- gg_2024_09_training.fna.gz +2 -2
- gg_2024_09_training.tsv.gz +2 -2
- gg_2024_09_training_ids.txt +0 -0
README.md
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This dataset contains 16S rRNA gene sequences with hierarchical taxonomic annotations, designed for training and evaluating models like DeepTaxa. It is a processed version of the Greengenes database, widely used in microbiome research.
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## Dataset Details
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## Usage
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Use with DeepTaxa:
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### Modifications
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This modified version (gg_2024_09) was created by the Systems Genomics Lab for use with DeepTaxa. The
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Copyright (c) 2025, Systems Genomics Lab
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For DeepTaxa: See [GitHub](https://github.com/systems-genomics-lab/deeptaxa).
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## Contact
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Report issues on [GitHub](https://github.com/systems-genomics-lab/deeptaxa/issues).
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This dataset contains 16S rRNA gene sequences with hierarchical taxonomic annotations, designed for training and evaluating models like DeepTaxa. It is a processed version of the Greengenes database, widely used in microbiome research.
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## Dataset Details
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The dataset includes the following files:
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| File Name | Type | Number of Sequences | Size |
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| `gg_2024_09_training.fna.gz` | FASTA (sequences) | 277,336 | ~96.4 MB |
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| `gg_2024_09_training.tsv.gz` | TSV (taxonomy labels) | 277,336 | ~2.6 MB |
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| `gg_2024_09_testing.fna.gz` | FASTA (sequences) | 69,335 | ~24.1 MB |
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| `gg_2024_09_testing.tsv.gz` | TSV (taxonomy labels) | 69,335 | ~0.8 MB |
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| `gg_2024_09_training_ids.txt` | Text (sequence IDs) | 277,336 | - |
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| `gg_2024_09_testing_ids.txt` | Text (sequence IDs) | 69,335 | - |
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- **Format**: FASTA for sequences (compressed), TSV for labels with 7 taxonomic levels (compressed).
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- **Source**: Derived from Greengenes (DeSantis et al., 2006), downloaded from https://ftp.microbio.me/greengenes_release/2022.10/
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## Usage
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Use with DeepTaxa:
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### Modifications
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This modified version (gg_2024_09) was created by the Systems Genomics Lab for use with DeepTaxa. The Greengenes database, downloaded from https://ftp.microbio.me/greengenes_release/2022.10/, was processed as follows:
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1. The original dataset, containing 23,450,269 sequences, was downloaded.
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2. Missing taxonomic classifications were filled with "Unclassified."
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3. Sequences were filtered to retain only those with at least 300 nucleotides, resulting in 354,023 sequences.
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4. Sequence IDs were extracted, and the taxonomy table was filtered to match these IDs, yielding 346,671 entries (7,352 IDs not found were noted).
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5. A clean ID list was generated from the filtered taxonomy table (346,671 IDs).
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6. Sequences were filtered to match the clean ID list, retaining 346,671 sequences.
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7. The dataset was split into training (277,336 sequences) and testing (69,335 sequences) sets using an 80:20 ratio and a fixed random seed.
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8. Training and testing sequence IDs were extracted (277,336 and 69,335 IDs, respectively).
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9. The taxonomy table was filtered to create separate training (277,336 rows) and testing (69,335 rows) label files.
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These steps ensured the dataset was cleaned, filtered, and split for use with DeepTaxa.
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Copyright (c) 2025, Systems Genomics Lab
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For DeepTaxa: See [GitHub](https://github.com/systems-genomics-lab/deeptaxa).
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## Contact
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Report issues on [GitHub](https://github.com/systems-genomics-lab/deeptaxa/issues).
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gg_2024_09_testing.fna.gz
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gg_2024_09_testing.tsv.gz
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gg_2024_09_training.fna.gz
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gg_2024_09_training.tsv.gz
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gg_2024_09_training_ids.txt
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