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  • Workflow for database creation
  • Automation of this steps
  • Creating a custom version of pATLAS
  1. API

Database creation

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Last updated 6 years ago

Workflow for database creation

1) Download plasmid sequences available in .

2) Extract fasta from tar.gz.

4) Clone this repository:

git clone https://github.com/tiagofilipe12/pATLAS

6) Configure the database:

createdb <database_name>
pATLAS/patlas/db_manager/db_create.py <database_name>
# e.g.
abricate --db card <master_fasta*.fas> > abr_card.tsv
abricate --db resfinder <master_fasta*.fas> > abr_resfinder.tsv
abricate --db vfdb <master_fasta*.fas> > abr_vfdb.tsv
abricate --db plasmidfinder <master_fasta*.fas> > abr_plasmidfinder.tsv
# e.g.
abricate2db.py -i abr_plasmidfinder.tsv -db plasmidfinder \
    -id 80 -cov 90 -csv aro_index.csv -db_psql <database_name>

Automation of this steps

Creating a custom version of pATLAS

3) Download and extract , which will be fed to pATLAS.

5) Install its

7) run - the output will include a filtered. fasta file (master_fasta_*.fas).

8) run , with CARD, ResFinder, PlasmidFinder, VFDB databases.

9) Download the necessary for the abricate2db.py script (aro_index.csv).

10) Update the git submodules (git submodule update --init --recursive) and run - using all the previous tsv as input.

11) .

This steps are fully automated in the nextflow pipeline .

If you require to add your own plasmids to pATLAS database without asking to add them to , you can provide custom fasta files when building the database using the -i option of . Then follow the steps .

NCBI taxonomy
dependencies
MASHix.py
ABRicate
card index
abricate2db.py
pATLAS-db-creation
dump database to a sql file
pATLAS website
MASHix.py
described above
NCBI refseq
Workflow db creation