Skip to main content

Ranking the risk of antibiotic resistance for genomes/metagenomes

Project description

arg_ranker

arg_ranker evaluates the risk of ARGs in genomes and metagenomes

Install

pip install arg_ranker

Requirement

  • python 3
  • kraken2: conda install -c bioconda kraken2
    download kraken2 database: kraken2-build --standard --db $KRAKENDB
    where $krakenDB is your preferred database name/location\
  • diamond: conda install -c bioconda diamond\
  • blast+: conda install -c bioconda blast

How to use it

  • put all your genomes (.fa or .fasta) and metagenomes (.fq or .fastq) into one folder ($INPUT)
  • run arg_ranker -i $INPUT --kkdb $KRAKENDB
  • run sh arg_ranking/script_output/arg_ranker.sh

Output

  • Sample_ranking_results.txt (Table 1)

    Sample Rank_I_abu Rank_II_abu Rank_III_abu Rank_IV_abu Unassessed_abu Total_abu Rank_code Rank_I_risk Rank_II_risk Rank_III_risk Rank_IV_risk ARGs_unassessed_risk note1
    WEE300_all-trimmed-decont_1.fastq 2.9E-02 0.0E+00 7.4E-02 7.8E-01 1.2E-01 4.2E-04 1.0-0.0-0.5-1.7-0.3 1.0 0.0 0.5 1.7 0.3 hospital_metagenome
    EsCo_genome.fasta 0.0E+00 0.0E+00 0.0E+00 1.0E+00 0.0E+00 2.0E+00 0.0-0.0-0.0-2.2-0.0 0.0 0.0 0.0 2.2 0.0 E.coli_genome
  1. We compute the abundance of ARGs as the copy number of ARGs divided by the 16S copy number in a sample
    Rank_I - Unassessed_abu: total abundance of ARGs of a risk rank
    Total_abu: total abundance of all ARGs
  2. We compute the risk of ARGs as the average abundance of ARGs of a risk rank divided the average abundance of all ARGs
    Rank_I_risk - Unassessed_risk: the risk of ARGs of a risk rank
    Rank_code: a code of ARG risk from Rank I to Unassessed
  • Sample_ARGpresence.txt:
    The abundance, the gene family, and the antibiotic of resistance of ARGs detected in the input samples

Test

run arg_ranker -i example --kkdb $KRAKENDB
run sh arg_ranking/script_output/arg_ranker.sh
The arg_ranking/Sample_ranking_results.txt should look like Table 1

Metadata for your samples (optional)

arg_ranker can merge your sample metadata into the results of ARG ranking (i.e. note1 in Table 1).
Simply put all information you would like to include into a tab-delimited table
Make sure that your sample names are listed as the first column (check example/metadata.txt).

Copyright

Dr. An-Ni Zhang (MIT), Prof. Eric Alm (MIT), Prof. Tong Zhang* (University of Hong Kong)

Citation

  1. Zhang AN, ..., Alm EJ, Zhang T: Choosing Your Battles: Which Resistance Genes Warrant Global Action? (bioRxiv coming soon)
  2. Yang Y, ..., Tiedje JM, Zhang T: ARGs-OAP: online analysis pipeline for antibiotic resistance genes detection from metagenomic data using an integrated structured ARG-database. Bioinformatics 2016.

Contact

anniz44@mit.edu or caozhichongchong@gmail.com

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

arg_ranker-2.6.tar.gz (6.3 kB view details)

Uploaded Source

Built Distribution

arg_ranker-2.6-py3.6.egg (90.9 MB view details)

Uploaded Egg

File details

Details for the file arg_ranker-2.6.tar.gz.

File metadata

  • Download URL: arg_ranker-2.6.tar.gz
  • Upload date:
  • Size: 6.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.8.0 tqdm/4.32.2 CPython/3.6.7

File hashes

Hashes for arg_ranker-2.6.tar.gz
Algorithm Hash digest
SHA256 ed17a0e717bd7f6cd1176364bf5c466054af05384c34858e06f10a65d8795590
MD5 69e70ceb42efde33406e05edad51c9d1
BLAKE2b-256 021e09254fb449bb2e9443da742a23589a19508a4d67a8e778e059ff417c6b53

See more details on using hashes here.

File details

Details for the file arg_ranker-2.6-py3.6.egg.

File metadata

  • Download URL: arg_ranker-2.6-py3.6.egg
  • Upload date:
  • Size: 90.9 MB
  • Tags: Egg
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.8.0 tqdm/4.32.2 CPython/3.6.7

File hashes

Hashes for arg_ranker-2.6-py3.6.egg
Algorithm Hash digest
SHA256 8a357e3b01e61b12b04ede81777e0c12911447d4487fd0ec604ce63563bfef0d
MD5 124d951aaf237079e7f4f9c68d81ad51
BLAKE2b-256 e623c149f82990df1013820775336e27dd0bca3c8eb90d394e56f8f96e8b1a98

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page