3. Use existing GTax database metadata in Python

Download current Python objects in pickle format from GCP. Find latest version from: https://console.cloud.google.com/storage/browser/gtax-database/

localhost:~> gsutil -u <your-GCP-project-ID> -m cp gs://gtax-database/<latest_version>/fasta/taxonomy.pickle .
localhost:~> gsutil -u <your-GCP-project-ID> -m cp gs://gtax-database/<latest_version>/fasta/taxonomy_groups.pickle .

Loading data in Python

from gtax.taxonomy import Taxonomy
taxonomy = Taxonomy(tax_pickle_file='taxonomy.pickle', group_pickle_file = 'taxonomy_groups.pickle')

Output:

2464341 taxonomies loaded
bacteria Node: 537498 Sequences: 19435
archaea Node: 14266 Sequences: 798
liliopsida Node: 48464 Sequences: 317
eudicotyledons Node: 153108 Sequences: 1077
viridiplantae Node: 48003 Sequences: 185
fungi Node: 186994 Sequences: 914
arthropoda Node: 912789 Sequences: 2596
neoteleostei Node: 31205 Sequences: 1610
actinopterygii Node: 22514 Sequences: 1258
glires Node: 5490 Sequences: 2346
primates Node: 1101 Sequences: 673
carnivora Node: 783 Sequences: 437
artiodactyla Node: 1200 Sequences: 487
amphibia Node: 13009 Sequences: 122
sauropsida Node: 32051 Sequences: 1476
sarcopterygii Node: 4941 Sequences: 376
chordata Node: 4122 Sequences: 400
eukaryota Node: 194114 Sequences: 896
viruses Node: 234108 Sequences: 14233

3.1. Raw files

3.1.1. FASTA and taxonomy maps

localhost:~> gsutil -u <your-GCP-project-ID> -m cp gs://gtax-database/<latest_version>/fasta .

3.1.2. BLAST databases

localhost:~> gsutil -u <your-GCP-project-ID> -m cp gs://gtax-database/<latest_version>/blastdb .

3.1.3. Kraken2 databases

localhost:~> gsutil -u <your-GCP-project-ID> -m cp gs://gtax-database/<latest_version>/kraken2 .