Skip to main content

Running AMRFinderPlus for MDU

Project description

abriTAMR

CircleCI

Taming the AMR beast

abriTAMR is an AMR gene detection pipeline that runs AMRFinderPlus on a single (or list ) of given isolates and collates the results into a table, separating genes identified into functionally relevant groups.

abriTAMR is accredited by NATA for use in reporting the presence of reportable AMR genes in Victoria Australia.

New look in v 1.0.0

  • Acquired resistance mechanims in the form of point mutations (restricted to subset of species)
  • Streamlined output.
  • Presence of virulence factors

Install

abriTAMR requires AMRFinder Plus, this can be installed with conda alone or as part of the abriTAMR conda installation (see below).

conda create -n abritamr -c bioconda ncbi-amrfinder
conda activate abritamr
amrfinder -U (to download and install recent DB)
pip3 install abritamr

Command-line tool

abritamr run --help

optional arguments:
  -h, --help            show this help message and exit
  --contigs CONTIGS, -c CONTIGS
                        Tab-delimited file with sample ID as column 1 and path
                        to assemblies as column 2 OR path to a contig file
                        (used if only doing a single sample - should provide
                        value for -pfx). (default: )
  --prefix PREFIX, -px PREFIX
                        If running on a single sample, please provide a prefix
                        for output directory (default: abritamr)
  --species {Acinetobacter_baumannii,Campylobacter,Enterococcus_faecalis,Enterococcus_faecium,Escherichia,Klebsiella,Salmonella,Staphylococcus_aureus,Staphylococcus_pseudintermedius,Streptococcus_agalactiae,Streptococcus_pneumoniae,Streptococcus_pyogenes,Vibrio_cholerae}, -sp {Acinetobacter_baumannii,Campylobacter,Enterococcus_faecalis,Enterococcus_faecium,Escherichia,Klebsiella,Salmonella,Staphylococcus_aureus,Staphylococcus_pseudintermedius,Streptococcus_agalactiae,Streptococcus_pneumoniae,Streptococcus_pyogenes,Vibrio_cholerae}
                        Set if you would like to use point mutations, please
                        provide a valid species. (default: )
  --jobs JOBS, -j JOBS  Number of AMR finder jobs to run in parallel.
                        (default: 16)

You can also run abriTAMR in mdu mode, this will output a spreadsheet which is based on reportable/not-reportable requirements in Victoria. You will need to supply a quality control file (comma separated) (-q), with the following columns:

  • ISOLATE
  • SPECIES_EXP (the species that was expected)
  • SPECIES_OBS (the species that was observed during the quality control analysis)
  • TEST_QC (PASS or FAIL)

--sop refers to the type of collation and reporting pipeline

  • general
    • standard reporting structure for aquired genes, output as reportable and non-reportable
  • salmonella
    • Inferred AST based on validation undertaken at MDU
  --qc QC, -q QC        Name of checked MDU QC file. (default: )
  --runid RUNID, -r RUNID
                        MDU RunID (default: Run ID)
  --matches MATCHES, -m MATCHES
                        Path to matches, concatentated output of abritamr
                        (default: summary_matches.txt)
  --partials PARTIALS, -p PARTIALS
                        Path to partial matches, concatentated output of
                        abritamr (default: summary_partials.txt)
  --sop {general,salmonella}
                        The MDU pipeline for reporting results. (default:
                        general)

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

abritamr-1.0.4.tar.gz (2.8 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

abritamr-1.0.4-py3-none-any.whl (2.0 MB view details)

Uploaded Python 3

File details

Details for the file abritamr-1.0.4.tar.gz.

File metadata

  • Download URL: abritamr-1.0.4.tar.gz
  • Upload date:
  • Size: 2.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.10

File hashes

Hashes for abritamr-1.0.4.tar.gz
Algorithm Hash digest
SHA256 f6877a464c7d377b729b6238945dd285f94418118a3ca3a646b15e0bd5adbb3c
MD5 57b8eee81637133ad356ecc4d5436f68
BLAKE2b-256 4805c7610c066e0fa95d2cee96ace62d46d66a151a7cdf369dd337a6857d71e9

See more details on using hashes here.

File details

Details for the file abritamr-1.0.4-py3-none-any.whl.

File metadata

  • Download URL: abritamr-1.0.4-py3-none-any.whl
  • Upload date:
  • Size: 2.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.10

File hashes

Hashes for abritamr-1.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 c7d7cbb73644b177ba52be96a5f6500025516e7ef3743aea634fc2087361ed35
MD5 0a0480a6d834e94b67454c714c92a756
BLAKE2b-256 f2f06afca3046eaf860753fa048d0f596af0c763461588d4145d8bfad7d2775d

See more details on using hashes here.

Supported by

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